Interactive device-based teaching of language

ABSTRACT

Methods, computer program products, and systems are presented. The method, computer program products, and systems can include, for instance: providing to a student user prompting data, wherein the prompting data prompts the student user to enter into an electronic teaching device voice data defining a correct pronunciation for a certain alphabet letter of a language alphabet, and wherein the prompting data prompts the student user to electronically enter handwritten data into the electronic teaching device defining a correct drawing of the certain alphabet letter; and examining response data received from the student user in response to the prompting data.

BACKGROUND

Artificial intelligence (AI) refers to cognitive intelligence exhibitedby machines. Artificial intelligence (AI) research includes search andmathematical optimization, neural networks and probability. Artificialintelligence (AI) solutions involve features derived from research in avariety of different science and technology disciplines ranging fromcomputer science, mathematics, psychology, linguistics, statistics, andneuroscience. Machine learning has been described as the field of studythat gives computers the ability to learn without being explicitlyprogrammed.

SUMMARY

Shortcomings of the prior art are overcome, and additional advantagesare provided, through the provision, in one aspect, of a method. Themethod can include, for example: providing to a student user promptingdata, wherein the prompting data prompts the student user to enter intoan electronic teaching device voice data defining a correctpronunciation for a certain alphabet letter of a language alphabet, andwherein the prompting data prompts the student user to electronicallyenter handwritten data into the electronic teaching device defining acorrect drawing of the certain alphabet letter; examining response datareceived from the student user in response to the prompting data; andbased on the examining indicating that the student user has correctlypronounced and drawn the certain alphabet letter, providing to thestudent user next prompting data, wherein the next prompting dataprompts the student user to correctly pronounce a next alphabet letter,wherein the next prompting data prompts the student user to correctlydraw the next alphabet letter, the next alphabet letter being successiveto the certain alphabet letter in the language alphabet.

In another aspect, a computer program product can be provided. Thecomputer program product can include a computer readable storage mediumreadable by one or more processing circuit and storing instructions forexecution by one or more processor for performing a method. The methodcan include, for example: providing to a student user prompting data,wherein the prompting data prompts the student user to enter into anelectronic teaching device voice data defining a correct pronunciationfor a certain alphabet letter of a language alphabet, and wherein theprompting data prompts the student user to electronically enterhandwritten data into the electronic teaching device defining a correctdrawing of the certain alphabet letter; examining response data receivedfrom the student user in response to the prompting data; and based onthe examining indicating that the student user has correctly pronouncedand drawn the certain alphabet letter, providing to the student usernext prompting data, wherein the next prompting data prompts the studentuser to correctly pronounce a next alphabet letter, wherein the nextprompting data prompts the student user to correctly draw the nextalphabet letter, the next alphabet letter being successive to thecertain alphabet letter in the language alphabet.

In a further aspect, a system can be provided. The system can include,for example a memory. In addition, the system can include one or moreprocessor in communication with the memory. Further, the system caninclude program instructions executable by the one or more processor viathe memory to perform a method. The method can include, for example:providing to a student user prompting data, wherein the prompting dataprompts the student user to enter into an electronic teaching devicevoice data defining a correct pronunciation for a certain alphabetletter of a language alphabet, and wherein the prompting data promptsthe student user to electronically enter handwritten data into theelectronic teaching device defining a correct drawing of the certainalphabet letter; examining response data received from the student userin response to the prompting data; and based on the examining indicatingthat the student user has correctly pronounced and drawn the certainalphabet letter, providing to the student user next prompting data,wherein the next prompting data prompts the student user to correctlypronounce a next alphabet letter, wherein the next prompting dataprompts the student user to correctly draw the next alphabet letter, thenext alphabet letter being successive to the certain alphabet letter inthe language alphabet.

Additional features are realized through the techniques set forthherein. Other embodiments and aspects, including but not limited tomethods, computer program product and system, are described in detailherein and are considered a part of the claimed invention.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more aspects of the present invention are particularly pointedout and distinctly claimed as examples in the claims at the conclusionof the specification. The foregoing and other objects, features, andadvantages of the invention are apparent from the following detaileddescription taken in conjunction with the accompanying drawings inwhich:

FIG. 1 depicts a system having a manager system, an administrator clientcomputer device, electronic teaching devices, client computer devices, adictionary service system, and a social media system according to oneembodiment;

FIGS. 2A-2B depict a physical form view of electronic teaching deviceaccording to one embodiment;

FIG. 3A is a flowchart illustrating a method for performance by amanager system interoperating with other components according to oneembodiment;

FIG. 3B depicts a user interface for display on a display of anadministrator client computer device according to one embodiment;

FIG. 3C depicts a user interface for display on a display of anelectronic teaching device or a user client computer device according toone embodiment;

FIGS. 4A-4R depict operations of an electronic teaching device duringperformance of a teaching session according to one embodiment;

FIG. 5A and 5B depict predictive models trained by machine learningprocesses according to one embodiment;

FIG. 6 depicts a computing node according to one embodiment;

FIG. 7 depicts a cloud computing environment according to oneembodiment; and

FIG. 8 depicts abstraction model layers according to one embodiment.

DETAILED DESCRIPTION

System 100 for use in teaching students in respect to spoken and writtenalphabet letters is shown in FIG. 1. System 100 can include managersystem 110 having an associated data repository 108, administratorclient computer device 120, electronic teaching devices 130A-130Z,dictionary service system 140, and social media system 150. Managersystem 110, administrator client computer device 120, electronicteaching devices 130A-130Z, dictionary service system 140, and socialmedia system 150 can be in communication with one another via network180.

Manager system 110, administrator client computer device 120, electronicteaching devices 130A-130Z, dictionary service system 140, and socialmedia system 150 can be provided by computing node based systems anddevices connected by network 180. Network 180 can be a physical networkand/or a virtual network. A physical network can be for example aphysical telecommunications network connecting numerous computing nodesor systems such as computer servers and computer clients. A virtualnetwork can, for example, combine numerous physical networks or partsthereof into a logical virtual network. In another example, numerousvirtual networks can be defined over a single physical network.

In one embodiment, manager system 110 can be external to administratorclient computer device 120, electronic teaching devices 130A-130Z,dictionary service system 140, and social media system 150. In anotherembodiment, manager system 110 can be collocated with one or more ofadministrator client computer device 120, electronic teaching devices130A-130Z, dictionary service system 140, and/or social media system150.

Each of the different electronic teaching devices 130A-130Z can beassociated to a different user. Electronic teaching devices according toone embodiment can be a computing node device having a specialized formfactor an example of which is described in FIGS. 2A and 2B. Regardingone or more client computer device 130A-130Z, a computer device of oneor more client computer device 130A-130Z in one embodiment can be acomputing node device provided by a client computer, e.g. a mobiledevice, e.g. a smartphone or tablet, a laptop, smartwatch or PC thatruns one or more program, e.g. including a web browser for opening andviewing web pages. Each of the different client computer devices135A-135Z can be associated to a different user. Regarding one or moreclient computer device 135A-135Z, a computer device of one or moreclient computer device 135A-135Z in one embodiment can be a computingnode device provided by a client computer, e.g. a mobile device, e.g. asmartphone or tablet, a laptop, smartwatch or PC that runs one or moreprogram, e.g. including a web browser for opening and viewing web pages.

Social media system 150 can include a collection of files, including forexample, HTML files, CSS files, image files, and JavaScript files.Social media system 150 can be a social website such as FACEBOOK®(Facebook is a registered trademark of Facebook, Inc.), TWITTER®(Twitter is a registered trademark of Twitter, Inc.), LINKEDIN®(LinkedIn is a registered trademark of LinkedIn Corporation), orINSTAGRAM® (Instagram is a registered trademark of Instagram, LLC).Computer implemented social networks incorporate messaging systems thatare capable of receiving and transmitting messages to client computersof participant users of the messaging systems. Messaging systems canalso be incorporated in systems that that have minimal or no socialnetwork attributes. A messaging system can be provided by a shortmessage system (SMS) text message delivery service of a mobile phonecellular network provider, or an email delivery system. Manager system110 can include a messaging system in one embodiment. During a processof registration wherein a user of system 100 registers as a registereduser of system 100, a user sending registration data can send withpermission data defining the registration data a permission that grantsaccess by manager system 110 to data of the user within social mediasystem 140. On being registered, manager system 110 can examine data ofsocial media system 150 e.g. to determine whether first and second usersare in communication with one another via a messaging system of socialmedia system 150. A user can enter registration data using a userinterface displayed on a client computer device of electronic teachingdevices 130-130Z or client computer devices 135A-135Z. Enteredregistration data can include e.g. name, address, social media accountinformation, other contact information, biographical information,background information, preferences information, and/or permissions datae.g. can include permissions data allowing manager system 110 to querydata of a social media account of a user provided by social media system140 including messaging system data and any other data of the user. Whena user opts-in to register into system 100 and grants system 100permission to access data of social media system 150, system 100 caninform the user as to what data is collected and why, that any collectedpersonal data may be encrypted, that the user can opt out at any time,and that if the user opts out, any personal data of the user is deleted.

Data repository 108 of manager system 110 can store various data. Inusers area 2121 data repository 108 can store data on users of system100. On registration of a user into system 100 manager system 110 canassign a Universally Unique Identifier (UUID) to each new user. Alongwith the UUID for each user, there can be stored in users area 2121,e.g. the name of each user, friendly names for respective users,demographic data for respective users, contact data for respectiveusers, and the like.

In languages area 2122 data repository 108 can store dictionary data forsupport of one or more language. System 100 can be configured to teachusers in respect to spoken and written letters of one or more alphabet.System 100 can be configured so that system 100 teaches users in respectto one or more language. System 100 can be configured so that managersystem 110 iteratively queries data from dictionary service system 140.Dictionary service system 140 can be configured to provide dictionaryservices in one or more language. Dictionary services can includeservices that provide data specifying proper pronunciation andannunciation of letters in different languages. Dictionary servicesystem 140 can also provide data specifying the proper formation ofalphabet letters in one or more language.

Data repository 108 in stroke map area 2123 can include data specifyinga stroke sequence defining the proper formation of respective letters inone or more alphabet associated to one or more language. Manager system110 can obtain data for storage into stroke map area 2123 from multiplesources. According to one embodiment, administrator client computerdevice 120 can display a user interface that allows an administrator todefine stroke map data. A stroke map herein can refer to a sequence ofstrokes used to define an alphabet letter. For a respective letter,there can be more than one stroke map, each stroke map for a respectiveletter defining a different sequence of strokes. Embodiments hereinrecognize that there are multiple ways in which a given alphabet lettercan be formed. For example, the English letter “A” can be formed withuse of any one of the following possible stroke sequence that can berepresented with stroke map data: 1. (strokemap1),(a) first strokedefining a left angled line from top center apex to lower left corner,(b) a second stroke defining a right angled line from a top center apexto lower right corner, (c) a third stroke defining a horizontal lineextending left to right connecting the left angled line to the rightangled line; 2. (strokemap2), (a) lower left corner to top center apex,(b) top apex to lower right corner, (c) horizontal line extending leftto right connecting left angled line to right angled line, 3.(strokemap3), (a) horizontal line extending right to left, (b) rightline extending from lower right corner to top apex and touchinghorizontal line, (c) left line extending from lower left corner to topcenter apex and touching left side of horizontal line. Embodimentsherein recognize, based on the described example for the Englishalphabet letter “A”, that multiple stroke maps can be provided for eachrespective alphabet letter.

The user interface for display on administrator client computer device120 for use in defining stroke map data can present to administratoruser prompting data that prompts the administrator user to inputgraphical data that defines stroke maps and which can permit theadministrator user for respective letters, multiple stroke maps.

Manager system 110 can be configured to obtain stroke map data forpopulating stroke map area 2123 by use of alternative processes. Forexample, manager system 110 can be configured to iteratively querysocial media system 150 for input data that is input by users of socialmedia system 150 with use of a user interface adapted for electronicinput of handwritten data. According to one embodiment, manager system110 for populating data of stroke map area 2123 can examineelectronically input handwritten letters entered by users of electronicteaching devices 130A-130Z and/or client computer devices 135A-135Z,e.g. when such users are engaging in conversations mediated by socialmedia system 150. Electronic teaching devices 130A-130Z and/or clientcomputer devices of client computer devices 135A-135Z can have, e.g. atouchpad for input of handwritten data and manager system 110 canmonitor and examine such handwritten data to learn stroke sequences inpopular use by a population for defining of alphabet letters. Managersystem 110 can be configured to iteratively query electronically inputhandwritten data received from electronic teaching devices 130A-130Zand/or client computer devices 135A-135Z to learn stroke sequences inpopular use by users of system 100 and when learning a new strokesequence, manager system 110 can register a newly identified strokesequence as a stroke map for a given letter for storage into stroke maparea 2123. Social media data, according to one example, can includeelectronically input handwritten data which can be examined by managersystem 110 to determine stroke maps for storage into stroke map area2123 as set forth herein.

Stroke map area 2123 for a respective letter of an alphabet of a certainlanguage can store one or more stroke map. According to one use case,each stroke map for a given letter can be provided as a candidate strokemap for deployment in a teaching run mode of operation.

Users of system 100 can include, e.g. student users and guardian users,which guardian users can be associated to student users. According toone use case, student users of system 100 can be children or otherstudent users seeking improvement in language skills. A guardian usercan be associated to a student user. Registration of a user, accordingto one scenario, more than one user can be registered. For example, whenstudent user registration data, guardian user data can contemporaneouslybe obtained by manager system 110 for storage into users area 2121. Datastored in users area 2121 can include registration data such as, contactdata, name data, preferences data, and permissions data. One example ofpermissions data can include permissions specifying that manager system110 is permitted to examine social media data of a registered user.

Data repository 108 in history area 2124 can store historical data thatrecords data of actions by users in use of system 100. For example,instances or run modes of operation of system 100 can be specified asteaching sessions of system 100, in which system 100 is used forteaching a student. History data of history area 2124 can be organizedinto teaching sessions referenced to respective users. For example, arespective teaching session can have an associated user and can beassigned a UUID specific to the teaching session. Historical teachingsession data can include, e.g. data specifying a success or failure of astudent user in response to a challenge presented by manager system 110and include granular data such as high resolution voice clips receivedfrom a user in response to a pronunciation challenge presented bymanager system 110 and can include handwritten data entered by a user inresponse to a letter formation challenge presented to a user by managersystem 110.

Data repository 108 in decision data structures area 2125 can storedecision data structures, e.g. decision tables, decision trees forreturn of action decisions for use in teaching one or more student. Datarepository 108 in models area 2126 can store one or more predictivemodel that can be trained with use of machine learning training Thepredictive model stored in models area 2126 can include for example apredictive model that predicts that best performing stroke map for usein teaching a student user.

Manager system 110 can run various processes. Manager system 110 runningteaching process 112 can include manager system 110 presenting a userwith a test which can comprise a sequence of challenges defined byprompting data. A sequence of challenges can include for a givenalphabet letter (a) a letter pronunciation challenge; (b) a handwrittenletter formation challenge; and (c) a combined pronunciation andhandwritten letter formation challenge. Manager system 110 runningteaching process 112 can include manager system 110 deploying thesequence of challenges (a), (b), and (c) referenced herein for anordered sequence of alphabet letters starting with a first letter of analphabet. For example, for the English language, the sequence ofchallenges (a), (b) and (c) can initially be deployed to a user for theinitial alphabet letter “A” and can then proceed to the alphabet letter“B”, and then to “C”, and so on. Manager system 110 running teachingprocess 112 can include manager system 110 running associated supportingprocesses such as speech evaluation process 113 and letter evaluationprocess 114.

Manager system 110 running speech evaluation process 113 can use datafrom languages area 2122 of data repository 108. Manager system 110running speech evaluation process 113 can examine input voice data inputby a student user in reference to reference data which references aproper pronunciation for an alphabet letter. According to one example,manager system 110 running speech evaluation process 113 can examinevoice data input by a student user in reference to pronunciationreference data for the letter stored in languages area 2122 to return asimilarity score for the user input voice data. Where manager system 110determines that a score for input voice data of a student user exceeds athreshold, manager system 110 can return a determination that the userhas properly pronounced a letter for which manager system 110 haschallenged a user to enter a proper pronunciation.

Manager system 110 running letter evaluation process 114 can examineelectronically input handwritten data of a student user in reference tostroke map data stored for a certain letter in stroke map area 2123.Manager system 110 running letter evaluation process 114 can scoreelectronically input handwritten data input by a student user using anelectronic teaching device of electronic teaching devices 130A-130Z toreturn the similarity score, the input handwritten data as compared tostroked map data for a certain user. Manager system 110 in response to adetermination that a returned similarity score has exceeded a thresholdcan determine that a user has properly entered electronic handwrittendata to properly draw the alphabet letter having an associated strokemap data stored in stroke map area 2123.

Manager system 110 running machine learning process 115 can includemanager system 110 training one or more predictive model such as apredictive model for predicting a best performing stroke map for use inteaching a student user. For example, embodiments herein recognize thata respective alphabet letter can have multiple associated candidatestroke maps for deployment which can define candidate stroke maps fordeployment in a teaching session. The different stroke maps canrespectively represent different stroke sequences that can conceivablybe used for the formation of an alphabet letter. Over time, system 100can be configured to deploy for a given letter, multiple differentstroke maps and can apply teaching session data as training data fortraining a predictive model to predict a best performing stroke map fora given student user. Such a predictive model, once trained, can beresponsive to query data. Query data can include, e.g. skill level of auser. The skill level of a respective user of system 100 can beiteratively updated over time based on response data of a user receivedin response to challenges presented by manager system 110 duringteaching sessions. Query data can include, e.g. skill level of a usertogether with an identifier of a candidate stroke map. Predictive model5002 can return predicted performance data based on the skill level andstroke map identifier. Manager system 110 can apply several sets ofquery data comprising skill level data and stroke map identifier dataand can select the stroke map associated to the best predictedperformance.

Electronic teaching devices 130A-130Z can be configured as set forth inFIGS. 2A-2B, details of a physical configuration of electronic teachingdevice 130A are shown and described. Referring to FIGS. 2A and 2B,electronic teaching device 130A according to one embodiment can beconfigured as a bound book having a page 131 defined as a rigid flatpanel, second page 132 also defined as a rigid flat panel, wherein thefirst page 131 and the second page 132 are bound by a binding 133 thatbinds the first page 131 to the second page 132. FIG. 2A illustrateselectronic teaching device 130A in a closed configuration and FIG. 2Billustrates electronic teaching device 130A in an open configuration.Embodiments herein recognize that student users, such as childrenstudent users, can have a preference for physical books and thus theconfiguration as shown in FIGS. 2A-2B in physical book form wouldencourage engagement of a student user with electronic teaching device130A.

Referring to FIG. 2A, electronic teaching device 130A can include one ormore computing node 10 which is further described in connection withFIG. 6 herein. For example, electronic teaching device 130A can includecomputing node 10 distributed between first page 131 and second page132. According to one embodiment, electronic teaching device 130A caninclude computing node 10 disposed in first page 131 and secondcomputing node 10 disposed within second page 132 wherein each of thefirst page 131 and the second page 132 are provided by rigid panels. Oneor more computing node 10 of electronic teaching device 130A can includevarious devices such as one or more processor 16, one or more outputdevice 25, and one or more sensor 27. The one or more output device 25can include one or more display and/or one or more audio output device,e.g. speaker. The one or more input sensor 27 can include, e.g. one ormore touch panel for input of handwritten data and/or one or more audioinput device, e.g. speaker. According to one embodiment, one or morecomputing node 10 of electronic teaching device 130A can be provided bya RASPBERRY® PI® model computing node which is one form of a low powercomputing node that can advantageously provide connectivity in remoteareas with reduced power consumption (RASPBERRY® and PI® are registeredtrademarks of the Raspberry Pi Foundation).

Referring to FIG. 2B, showing electronic teaching device 130A in openconfiguration additional features are described. First page 131 andsecond page 132 can each comprise respective displays which can compriseone respective displays 131D and 132D which are visible when electronicteaching device 130A is in an open configuration as specified in FIG.2B. Respective displays 131D and 132D define instances of one or moreoutput device 25 as shown in FIG. 2A. According to one embodiment,display 131D of left page 131 can be configured differently than display132D of right page 132. The highlighted commercial environment of acomputing node can run various different operating systems including,e.g. UBUNTU MATE®, SNAPPY UBUNTU CORE®, and WINDOWS 10 IoT CORE™.(UBUNTU MATE® and SNAPPY UBUNTU CORE® are registered trademarks ofCanonical Ltd and WINDOWS 10 IoT CORE™ is a trademark of Microsoft,Inc.). The described computing node can be equipped with variousinterfaces for connectivity including, e.g. WIFI and Bluetooth.

With further reference to FIG. 2B, displays 131D and 132D can beconfigured differently. For example, display 131D can be configured as adisplay only display and display 132D can be configured as a displaywith an integrated touchscreen, therefore display 132D can define acombination of an output device 25 provided by a display and a sensor 27(FIG. 2A) defined by a touchscreen overlay. According to one embodiment,display 132D can be provided by an electronic paper (e-paper) basedtouchscreen display. E-paper display can emulate the appearance ofordinary ink on paper and thus can be engaging to a user. Many e-papertechnologies can hold static text and image indefinitely withoutelectrical power input and thus e-paper displays can feature reducedpower consumption. According to one embodiment, display 132D provided byan e-paper based touchscreen can include titanium dioxide particlesdispersed in a hydrocarbon oil.

According to further aspects described with respect to FIGS. 2A and 2B,first page 131 and second page 132 defining electronic teaching device130A can include respective magnets 131A disposed in first page 131 andsecond magnet 132A disposed in second page 132. The respective magnets131A and 132A can be disposed so that the respective magnets oppose oneanother when electronic teaching device 130A is in a closed bookconfiguration as described in connection with FIG. 2A. Magnets 131A and132A respectively, can be permanent magnets or transient magnets whichare magnetized on powerup of electronic teaching device 130A. Magnets131A and 132A can be configured so that magnets 131A and 132A areattracted to one another so that second page 132 and first page 131 tendto be pulled together when first page 131 and second page 132 are movedinto close proximity. The magnetic attracting force provided by magnets131A and 132A can be modest so that the attracting holding force can bebroken by the force provided by a student user such as a child andpulling first page 131 away from second page 132.

According to one embodiment, manager system 110 can be configured tosense changes in electrical communication between magnets 131A and 132A,which communication changes can be in dependence on the spacing betweenfirst page 131 and second page 132. Accordingly, manager system 110 bymonitoring of electrical communication between magnets 131A and 132A candetermine whether electronic teaching device 130A is in openconfiguration (FIG. 2B) or in open configuration (FIG. 2A). According toone embodiment, manager system 110 can be configured to initiate ateaching session in response to the determination that a student userhas opened electronic teaching device 130A to define the openconfiguration as depicted in FIG. 2B.

FIG. 3A depict a flowchart illustrating a method for performance bymanager system 110 interoperating with electronic teaching device 130A,systems 140 and 150, and administrator client computer device 120.Manager system 110 at block 1101 can be sending query data to systems140 and 150 for receipt by systems 140 and 150 at block 1401. Inresponse to the receipt of query data at block 1401, systems 140 and 150at block 1402 can send response data to manager system 110 for receiptby manager system 110 at block 1102.

With reference to FIG. 1, manager system 110 at block 1101 can bequerying dictionary service system 140, e.g. for updates on attributedata for one or more language supported by system 100 and can be sendingquery data to social media system 150, e.g. for samples ofelectronically input handwritten data for use by manager system 110,e.g. in populating stroke map area 2123 of data repository 108. At block1201, administrator client computer device 120 can be sendingconfiguration data for receipt by manager system 110 at block 1103.Configuration data sent at block 1201 can be configuration data definedby an administrator user using administrator user interface 3002, anexample of which is shown in FIG. 3C.

User interface 3002 as shown in FIG. 3C can be a displayed userinterface for display on a display of an administrator client computerdevice 120. In stroke map area 3004 of user interface 3002, anadministrator user can define data for populating stroke map area 2123of data repository 108. Using area 3004, an administrator user canspecify an alphabet letter of a supported language and can specify asequence of strokes for formulation of an alphabet letter. Userinterface 3002 can be a graphical user interface (GUI) that providesgraphical prompts to a user that prompts an administrator user to enter,e.g. with a stylus or finger a sequence of strokes, e.g. line segmentstrokes that define an alphabet letter. For example, for the letter “A”in the English language, a sequence of strokes defining the letter “A”can include (a) from top center apex to lower left corner, (b) from topcenter apex to lower right corner, and (c) a center horizontal lineconnecting the respective lines formed by (a) and (b). An administratoruser can define more than one stroke map for each letter of a supportedlanguage. In voice clips area 3006, an administrator user can entervoice clips for various purposes. For example, some voice clips can beentered to define a proper pronunciation of an alphabet letter, whichdata also or alternatively can be obtained from dictionary servicesystem 140. In settings area 3008 an administrator user can definesettings for a teaching session. The settings can include settingsdetermining, e.g. process flow, wait times, delay times, prompting data,e.g. positive and negating prompting data, e.g. positive prompting datafor presentment in the case that a user answers correctly to a challengeof negative prompting data defining a response in the case a userresponds incorrectly to a challenge and the like.

Manager system 110 in response to the receipt of administrator userdefined configuration data received at block 1103 can proceed to block1104. At block 1104 manager system 110 can determine if any usable datahas been received at block 1102 or block 1103 and can determine whethera teaching session should be reconfigured based on the received responsedata received at block 1102 and block 1103. In response to adetermination that there should be a reconfiguration of a teachingsessions manager system 110 can reconfigure a teaching session at block1104 based on the received response data at block 1102 and/or thereceived configuration data received at block 1103.

At block 1105, manager system 110 can send various data for receipt andstorage by data repository 108 at block 1081. The data sent for storageat block 1105 by manager system 110 can include, e.g. the raw responsedata received at block 1102 for population, e.g. of languages area 2122and/or stroke map area 2123 and the raw configuration data received atblock 1103 for population, e.g. of languages area 2122 and/or stroke maparea 2123 of data repository 108. The sent data sent by manager system110 at block 1105 additionally or alternatively can includeconfiguration setting data defining an updated configuration for ateaching session to be presented to a student user.

At block 1106, manager system 110 can be receiving registration datafrom electronic teaching device 130A which can be iteratively sendingregistration data at block 1301. The registration data can be defined bya student user and/or a guardian user with use of a displayed userinterface such as user interface 3022 depicted in FIG. 3C. Userinterface 3022 can be displayed on a display of electronic teachingdevice 130A and/or a client computer device such as client computerdevice 135A for use by a student user and/or a guardian user associatedto a student user.

User interface 3022 can be configured to permit a student user and/or aguardian user to enter various registration data. In area 3024 a studentand/or guardian user can enter contact information, e.g. specifyingname, address, e-mail account data, social media account data, phonenumber, and the like. In preferences area 3026 a student and/or guardianuser can enter such data as demographic user data specifying, e.g. age,gender, and observed preferences data of the user such as dataindicating recreational and/or entertainment activities enjoyed by theuser. In area 3028, a student and/or guardian user can enter permissionsdata specifying permissions of the user which permissions can includesuch permissions as permissions to permit manager system 110 to obtaindata from a social media account of a user via social media system 150.In response to receipt of registration data at block 1106, managersystem 110 can assign a UUID for each registered user and at block 1107can send registration data for storage into data repository 108. Inresponse to the sending by manager system 110 at block 1107, datarepository 108 can receive and store registration data, e.g. into usersarea 2121 at block 1082. In response to completion of block 1107,manager system 110 can proceed to block 1108.

At block 1108, manager system 110 can determine whether one or morecriterion has been satisfied for initiation of a teaching session start.At block 1108 manager system 110 according to one embodiment can bemonitoring electrical communication data between magnets 131A and 132Aas described in FIG. 2B for determining whether a student user hasopened an electronic teaching device into an open configuration asdepicted in FIG. 2B. In response to the determination that a studentuser has opened the electronic teaching device into an openconfiguration device (FIG. 2B) manager system 110 can commence ateaching session, which teaching session can comprise a sequence ofchallenges to a student user.

Referring to block 1108, manager system 110 can be iterativelyperforming block 1108 until one or more criterion for commencing ateaching session start are satisfied. In response to one or morecriterion for commencement of a teaching session start having beensatisfied manager system 110 can initiate stage I of a teaching sessionand proceed to block 1109.

At block 1109, manager system 110 can be sending prompting data toelectronic teaching device 130A for receipt and output by electronicteaching device 130A at block 1302. Prompting data received at block1302 and presented at block 1302 can include according to oneembodiment, the prompting data as depicted in FIGS. 4A-4C.

FIGS. 4A-4R depict a sequence of challenges defined by prompting datathat can be presented to a user by manager system 110 in the running ofa teaching session. FIG. 4A depicts electronic teaching device 130A inclosed configuration. FIG. 4B depicts electronic teaching device 130A inopen configuration. As described in connection with block 1108, managersystem 110 can be configured so that a teaching session is initiated inresponse to a user opening electronic teaching device 130A into an openconfiguration as depicted in FIG. 4B. Thus, with reference to FIGS. 4Aand 4B, electronic teaching device 130A can be configured so that when auser opens the electronic teaching device 130A into the openconfiguration (FIG. 4B) a teaching session is commenced as described inconnection with the flow from block 1108 to 1109 of the flowchart ofFIG. 3A. As described in connection with block 1109, manager system 110can send prompting data to electronic teaching device 130A in responseto a user opening the electronic teaching device 130A into an openconfiguration as depicted in FIG. 4B. Prompting data sent at block 1109can include prompting data as depicted in FIG. 4B. The prompting datacan include prompting data, which on receipt is presented in text formand/or in audio form. FIG. 4B depicts both a text presentment and anaudio presentment of prompting data. Prompting data received andpresented at block 1302 can include text based prompting data which canbe displayed on display 131D.

Referring to FIG. 4B presented prompting data can include text basedprompting data, e.g. the text “WELCOME USER!” presented in display 131Dof page 131 and also can include audio presented prompting data, e.g.the BOT audio annunciated prompting data of “WELCOME USER, TODAY WE AREGOING TO LEARN HOW TO PRONOUNCE AND WRITE LETTERS!”.

Referring again to the flowchart of FIG. 3A, manager system 110 caninitiate stage I of a teaching session at block 1109. Stage I of ateaching session can include presentment of challenges defined byprompting data to a user, wherein the one or more challenge is achallenge to properly pronounce an alphabet letter, e.g. starting withthe first letter of an alphabet being supported by system 100. Suchfirst stage processing is depicted in FIG. 4C. Prompting data depictedin FIG. 4D can be prompting data sent at block 1109 by manager system110 and received and presented by electronic teaching device 130A atblock 1302. Prompting data prompting a user to properly pronounce andalphabet letter as depicted in FIG. 4C can include text based promptingdata and audio based prompting data.

Referring to FIG. 4C, prompting data presented to a user can includeprompting data displayed on display 131D and can include the text baseddisplayed prompting data of the letter “A” which the user is beingprompted to pronounce. The text based prompting data presented ondisplay 131D can be accompanied by audio prompting data. The audioprompting data can be presented by an audio output device of electronicteaching device 130A and can comprise the voice synthesize promptingdata referenced to BOT. In reference to the BOT in FIG. 4C and caninclude the prompting data “PLEASE SAY THE LETTER A”.

Referring again to the flowchart of FIG. 3A, the user can respond to theprompting data received and presented at block 1302 at block 1303. Atblock 1303, electronic teaching device 130A can send response data sentin response to the received prompting data received at block 1302. Thesent response data sent at block 1303 can be received by manager system110 at block 1110. The response data can include, as depicted in FIG.4C, the student user 129A audibly presenting verbal response data whichis picked up by an audio input device of electronic teaching device 130Aand recorded as a voice clip and can be sent for evaluation as theaforementioned response data received by manager system 110 at block1110. The response data can be a voice clip representing audio spoken bystudent user 129A and specifying the users attempt to pronounce theletter in accordance with the prompting data presented to a user asdepicted in FIG. 4C. In response to the received response data at block1110, manager system 110 can proceed to block 1111.

At block 1111 manager system 110 can perform examining of the responsedata received at block 1110. Examining of the response data can includemultiple queries of data repository 108 as depicted by query receive andrespond block 1083 performed by data repository 108 as depicted in theflowchart of FIG. 3A. The examining at block 1111 by manager system 110can include examining the voice clip defining response data received atblock 1110 in reference to reference data that specifies a properpronunciation of the prompted for alphabet letter prompted with theprompting data presented as depicted in FIG. 4C. The referencepronunciation data can be stored in languages area 2122 of datarepository 108 and can be data previously obtained as set forth hereinfrom dictionary service system 140 and/or from configuration datadefined by a user using user interface 3002 as shown in FIG. 3B. Managersystem 110 performing examining at block 1111 can include manager system110 scoring the received voice clip data for similarity with thereference pronunciation data stored in languages area 2122 of datarepository 108. Manager system 110 can determine that a user hassuccessfully pronounced the prompted for letter prompted for with theprompting data described in FIG. 4C when the score assigned to the voiceclip exceeds a threshold.

Manager system 110 at block 1112 can determine whether one or morecriterion has been satisfied indicative of the user successfullypronouncing the prompted for letter for which proper pronunciation wasprompted for by the presentment of prompting data received and presentedat block 1302. As noted, one or more criterion at block 1112 can besatisfied based on a similarity score applied to received voice clipdata defining response data received at block 1110 exceeding athreshold. In response to a determination that the user has successfullypronounced the letter prompted for with prompting data sent at block1109, manager system 110 can proceed to block 1113.

In response to determination that a user has not successfully pronouncedthe prompted for letter manager system 110 at block 1112 can return toblock 1109 to iteratively send additional prompting data to prompt theuser to correctly pronounce the prompted for letter. In response to adetermination that a user at block 1112 has successfully pronounced theletter, manager system 110 as indicated, can proceed to block 1113 andcan present a positive reinforcing prompting data reinforcing to theuser that the user has successfully pronounced the prompted for letter.Positive reinforcing prompting data is depicted at FIG. 4D.

In reference to FIG. 4D, manager system 110 on the determination that auser has successfully pronounced a prompted for letter at block 1112 canproceed to block 1113 to send prompting data for receipt and presentmentby electronic teaching device 130A at block 1304. FIG. 4D depictsprompting data that can be sent by manager system 110 for receipt andpresentment by electronic teaching device 130A at block 1304. Theprompting data depicted in FIG. 4D can include prompting data,positively reinforcing to the user that the user has successfullypronounced the prompted for letter which was prompted for at block 1109.The positive reinforcement prompting data depicted as being presented inFIG. 4D can include graphical based prompting data, text based promptingdata, and/or audio based prompting data. The displayed text basedprompting data depicted as being presented in FIG. 4D can include thetext “WELL DONE” depicted as being displayed on display 131D. Thegraphical based prompting data depicted as being presented in FIG. 4Dcan include the smiley face which can be displayed on display 131D ofelectronic teaching device 130A. The audio based prompting data depictedas being presented in FIG. 4D can include electronic teaching device130A by an audio output device thereof presenting the audio positivereinforcing prompt defined by the output audio prompt “WELL DONE”presented for listening by a user 129A. It should be noted that managersystem 110 on the determination at block 1112 that the user has notsuccessfully pronounced a prompted for letter can send negativeprompting data to a user, e.g. during a next iteration of send block1109, in which prompting data is sent to electronic teaching device 130Afor presentment by electronic teaching device 130A at a next iterationof block 1302. Such negative prompting data can include negativereinforcement prompting data which can sensitively inform the user thatthe user has not been successful, but in a manner so as not todiscourage the user from further attempting to master the subject matterof the current teaching session. Negative reinforcing prompting datawhich can be presented to encourage the user can include, e.g. graphicalprompting data in the form of a smiley face similar to the form of FIG.4D, except that the smile may be less pronounced (e.g. a half smile).Negative reinforcing data can also include text based prompting data fordisplay on display 131D and/or audio based prompting data for output byan audio output device of electronic teaching device 130A, text basednegative reinforcing prompting data can include such text basedprompting data as “NICE TRY USER”, and negative reinforcing audiopresented prompting data can include electronic teaching device 130Aannunciating the audio prompt “NICE TRY USER”.

Referring again to the prompting data sent at block 1113 for receipt andpresentment by electronic teaching device 130A at block 1304, stage IIprompting data can include prompting data that prompts a user to enterelectronic handwritten text to properly write and form a promptedletter.

FIGS. 4E-4N depict prompting data sent at block 1113 for receipt andpresentment at block 1304 for prompting the user to correctly write andform an alphabet letter, e.g. starting with the first letter of analphabet such as the letter “A” in the English language. Prompting datadepicted as presented in FIG. 4E can include the letter “A” displayed ondisplay 131D in undashed normal form and can include a display ondisplay 132D the letter “A” in dashed form. The dashed form presentmentindicated to the user that the user is being prompted to complete theletter that is presented in dashed form on display 132D which can be,for example, a touchscreen display that is sensitive to the users touchby finger and/or stylus. Prompting data specified in FIG. 4E can beaccompanied by audio prompting data such as the audio prompt output byan audio output device of electronic teaching device 130A. The audioprompt of “NOW WE ARE GOING TO DRAW THE LETTER ‘A’”.

Referring to FIGS. 4F-4J, prompting data for presentment on electronicteaching device 130A can include prompting data that graphicallyanimates a time ordered sequence of keystrokes that can be performed bya user to properly draw a prompted for alphabet letter. FIGS. 4F-4Jdepict prompting data according to a stroke map defining the sequence ofstrokes, wherein the letter “A” is formed by the stroke sequence asfollows: (a) first stroke defining a left angled line from top centerapex to lower left corner, (b) a second stroke defining a right angledline from a top center apex to lower right corner, (c) a third strokedefining a horizontal line extending left to right connecting the leftangled line to the right angled line

As shown in FIGS. 4F-4J, display 132D can display animated time ordergraphical data that specifies to the user a correct order of strokes toform the letter “A” in accordance with the described stroke map.Referring to FIGS. 4F-4H a progression of screen displays can bedisplayed to indicate the correct formation of the left line segmentdefining the letter “A”. Referring to FIG. 4F, a small line segment ofthe left line of the letter “A” is displayed and then, with reference toFIG. 4G, a larger segment of the left line of the letter “A” isdisplayed and then, in FIG. 4H, the full portion of the left line of theletter “A” is displayed. Manager system 110 can display the screendisplays of FIGS. 4F-4H in sequence so that the user is informed as tothe precise manner in which a stroke can be performed to define the leftline of the letter “A”. Namely, commencing from the top center positionand moving downward in an angle to the left lower corner position.

It can be seen that there are many possible modifications of the processfor presentment of prompting data as depicted in FIGS. 4F-4H. Forexample, the growth over time of the left line of the letter “A” can bepresented with a larger number of screen displays, e.g. breaking downthe formation of the left line of the letter “A” into N segments asopposed to three segments as depicted in FIGS. 4F-4H or fewer screendisplays can be displayed. For example, the sequence of three screendisplays can be reduced to two screen displays, but still show the userthe correct progression of a stroke for the formation of the left angledline of the letter “A”.

FIG. 41 depicts formation of the right line of a letter “A”. Withreference to FIG. 41, with the horizontal center line of the letter “A”remaining in dashed form and the right line depicted in solid form, theuser is informed that the user for the correct formation of the letter“A” should draw the right line of the letter “A” after the left line ofthe letter “A” and before drawing the center horizontal line of theletter “A”. FIG. 41 is presented for brevity but in reality, thescreenshot depicted in FIG. 41 can be broken down and presented overseveral screenshots, such as screenshots that gradually show theformation of the right line of the letter “A” as depicted in FIG. 41growing over a series of screenshots. In the manner of the left line ofthe letter “A” depicted with the animated sequence of screenshots ofFIGS. 4F-4H.

Referring to FIG. 4J, the prompting data depicts to the user theformation of the horizontal line of the letter “A”. Prior to promptingdata of FIG. 4J being displayed, electronic teaching device 130A ondisplay 132D can present the letter “A” with the horizontal line thereofpresented in dashed form as presented in FIG. 41 so that it isreinforced to the user that the drawing of the horizontal line of theletter “A” is the final step in the correct formation of the letter “A”.

Referring to FIG. 4G, the display to the user of the prompting data ofFIG. 4J can be broken down into a sequence of screen displays whichillustrate in a manner described with reference to FIG. 4F-4H thegradual formation of the horizontal line of FIG. 4J progressing over aseries of screenshots to depict the particular manner in which akeystroke for formation of the horizontal line of the letter “A” is tobe performed. Namely, starting from the left position at the left lineof the letter “A” and progressing rightward over time so that the drawnhorizontal line connects to the right line of the letter “A” depicted inFIG. 4J.

According to one embodiment, manager system 110 can present the timeorder prompting data described in connection with FIGS. 4A-4Jiteratively N times, e.g. one time, two times, three times, or M timesto reinforce to the user the proper time order progression of strokesfor the formation of the letter “A” according to a certain keymap.According to another aspect, which is described in further detailherein, manager system 110 at block 1113 can select one keymap forguiding the formation of a letter out of a set of candidate stroke mapsfor the letter.

Now referring to FIG. 4K, after the user is presented iteratively thelesson depicted with the progression of FIGS. 4A-4J to reinforce theproper formation of the letter, the user is provided prompting data toprompt the user to initiate formation the letter for which a formationlesson was just presented. Referring to FIG. 4K, visible indicator 1321which can be provided by a flashing dot can be presented to a user aspart of the presented prompting data presented at block 1304. Visibleindicator 1321 prompts the user as to the location of a first stroke forthe formation of the letter “A” in accordance with the current strokemap for the letter “A”, which location as referenced in FIG. 4K is a topcenter position, in accordance with the prompting data presented inFIGS. 4F-4H, depicting the growth of the left line of the letter “A”from the top center position. The user, having just been presented alesson as to the formation of a letter “A” can draw, with electronicallyhand drawn line 1322, the first line of the letter “A”. Theelectronically hand drawn data input by the user as depicted in FIG. 4Lcan be sent by electronic teaching device 130A at block 1303 as responsedata for sending by electronic teaching device 130A at block 1303 forreceipt by manager system 110 at block 1114.

According to some embodiments, manager system 110 can be configured sothat visible indicator 1321 (and next described visible indicators 1323and 1325 as shown in FIG. 4M and 4L) progressively move responsively toa student user advancing the drawing of a letter line so that thevisible indicator e.g. flashing dot iteratively prompts the user byindicating to the user a next position to which the letter linecurrently being drawn needs to be advanced for correct completion ofdrawing of the letter line currently being drawn. Visible indicators1321, 1323, 1325 can be provided e.g. by flashing dots, brightened areasof a display, and or areas of a display displayed in a different color.

Manager system 110 can be examining the received response data receivedat block 1114 at examining block 1115. The examining of receivedresponse data received at block 1114 at block 1115 can include multiplequeries of stroke map data of stroke map area 2123 and therefore caninclude multiple queries of data repository 108 as depicted by queryreceive and respond block 1084 performed by data repository 108.

At block 1116, manager system 110 can be determining whether one or morecriterion is satisfied indicative of the user having properly formed theletter. In response to a determination that a user has not properlyformed a letter, manager system 110 can return to block 1113 toiteratively send additional prompting data to a user until the userproperly forms the prompted for letter.

Referring to FIG. 4L, manager system 110 at block 1116 can determinethat a user has drawn only a portion of the prompted for letter and notthe full letter and therefore, can return to block 1113 to iterativelysend additional prompting data prompting the user to continue drawingthe prompted for letter. On the determination, based on the examining atblock 1115, that a first line of a prompted for letter has been properlyformed, manager system 110 as depicted in FIG. 4L can present promptingdata defining visible indicator 132 e.g. provided by a flashing dotwhich specifies to the user the location for initiating a second strokefor defining a prompted for letter. In the described embodiment, thesecond stroke for the formation of the letter “A” is at the samelocation of the first stroke for the letter “A”. Namely, at a top centerlocation. Accordingly, visible indicator 1323 in the describedembodiment of FIG. 4L, can be presented at the top center locationdepicted in FIG. 4L. The user having just received the lesson for theproper formation of the letter “A” can then electronically hand draw theline 1324 depicted in FIG. 4M.

Manager system 110 at examining block 1115 can determine that the userhas successfully drawn the second line 1324 defining the letter “A”, andtherefore at a next iteration of send block 1113 can send prompting datafor presentment of the visible indicator 1325 depicted in FIG. 4M,depicting the proper start location of the third key stroke for definingthe letter “A” in accordance with the current stroke map, definingformation of the letter “A”. In response to the presentment of visibleindicator 1325, the user can be prompted to draw the third line definingthe prompted for letter “A”, namely the horizontal line connecting thefirst line and the second line.

As depicted in FIG. 4N, the user can electronically enter handwrittendata defining hand drawn horizontal line 1326, which electronicallyentered data can be sent as a next iteration of response data sent atblock 1305. During a next iteration of examining block at block 1115 inresponse to the most recent iteration of response data received at block1114, manager system 110 can determine that the user has properlywritten and formed the prompted for letter “A”. Accordingly, during anext iteration of block 1116, in which manager system 110 determineswhether one or more criterion has been satisfied for advancing to thenext stage, manager system 110 can determine that the user has properlyformed the prompted for letter “A”.

Manager system 110 at examining block 1115 can activate letterevaluation process 114 (FIG. 1). Manager system 110 running letterevaluation process 114 can examine electronically input handwritten dataof a student user in reference to stroke map data stored for a certainletter in stroke map area 2123. Manager system 110 running letterevaluation process 114 can score electronically input handwritten datainput by a student user using an electronic teaching device ofelectronic teaching devices 130A-130Z to return a similarity score thatindicates a similarity of input handwritten data as compared to strokemap data for a certain user. Manager system 110 in response to adetermination that a returned similarity score has exceeded a thresholdcan determine that a user has properly entered electronic handwrittendata to properly define the alphabet letter having an associated strokemap data stored in stroke map area 2123. In response to determining thata user has properly formed a prompted for letter at block 1116, managersystem 110 can proceed to block 1117.

At block 1117, manager system 110 can send next prompting data forreceipt and presentment by electronic teaching device 130A at block1306. The prompting data received and presented at block 1306 caninclude positive reinforcing prompting data to positively reinforce tothe user that the user has successfully electronically enteredhandwritten data properly forming a prompted for letter. The positivereinforcing prompting data presented at block 1306 can include promptingdata depicted in FIG. 40 and can include text based positive reinforcingprompting data, e.g. the text “WELL DONE!”, the graphical based positivereinforcing prompting data, e.g. the smiley face depicted in FIG. 40displayed on display 131D, and the audio based positive reinforcingprompting data, e.g. the audio prompt that can be output by electronicteaching device 130A of “WELL DONE!”.

At block 1117, manager system 110 can commence stage III processing inwhich manager system 110 prompts the user to enter audio datarepresenting the proper pronunciation of a prompted for letter togetherwith electronically entered handwritten data representing the properformation of the letter.

FIG. 4P illustrates prompting data presented at block 1306 for stage IIIchallenges presented to the user to prompt the user to enter audio datadefining a proper pronunciation of a letter together with electronicallyentered handwritten data depicting the proper formation of a letter. Theprompting data associated with stage III can take on many forms, but inone form can include high level prompting data which provides minimallevel of prompting to the user to pose a significant challenge to theuser to confirm that the user has retained the lessons of the previousprompting. In one embodiment, the prompting data of stage III processingcan progress over time going from high level prompting to more granularprompting if the user does not perform in a timely manner in response tothe high level prompting. According to one embodiment, as depicted inFIG. 4P depicting high level prompting, presented prompting datapresented at block 1306, can include a general high level prompt, whichis presented, e.g. only in audio form and can include an audio outputdevice of electronic teaching device 130A presenting the general audioprompt “NOW, PLEASE SAY AND DRAW THE LETTER ‘A’”. In response to thegeneral prompting, the user can enter response data into electronicteaching device 130A which can be sent at send block 1307 as responsedata for receipt by manager system 110 at block 1118. The response datareceived at block 1118 can include a combination of voice clipsassociated to voice inputs presented by a user in combination withelectronically entered handwritten data entered by a user in response tothe prompting data presented at block 1306 as depicted in FIG. 4P, whichprompting data can iteratively progress into more detailed forms overtime, in response to insufficient response data of the user.

At block 1119, manager system 110 can perform examining of response datareceived at block 1118. The examining by manager system 1119 can includemultiple queries of data repository 108 as depicted by query receive andrespond block 1085, performed by data repository 108.

At block 1120, manager system 110 can determine whether one or morecriterion has been satisfied indicating that the student user hassuccessfully completed the stage III processing, meaning that the userhas successfully entered audio data represented as a voice clip definingresponse data representing a proper pronunciation of the prompted forletter together with electronically entered handwritten datarepresenting proper formation of the letter. In response to thedetermination that the user has successfully presented a correctpronunciation of a letter in combination with a correct formation of theletter, manager system 110 can proceed to block 1121 to advance theletter of the current teaching session. For example, if a teachingsession has commenced with the letter “A” the advanced letter, advancedto block 1121, can be the letter “B” in the English language. Managersystem 110 can then proceed to block 1122.

At block 1122, manager system 110 can return to block 1109 where managersystem 110 can perform stage I processing, except now with respect tothe next letter in the English alphabet, e.g. the letter “B” where auser was previously most recently trained in respect to the letter “A”.

FIG. 4Q illustrates electronic teaching device 130A presenting promptingdata to a user in response to the received prompting data received ablock 1306. The prompting data illustrated in FIG. 4Q can prompt astudent user to both correctly speak and draw a letter. Prompting datapresented to a user, as indicated in FIG. 4Q, can include text basedprompting data and audio based prompting data. In response to thereceived prompting data received at block 1306, electronic teachingdevice 130A at block 1306 can present text based prompting data ondisplay 131D, e.g. this text based prompting data “SPEAK AND DRAW THELETTER ‘A’”, the audio based prompting data presented to user at block1306 can include the audio voice synthesized output of “SPEAK AND DRAWTHE LETTER ‘A’”, as indicated in FIG. 4Q. In response to the promptingdata, the student user can electronically enter handwritten data to handdraw the letter “A” onto display 132D which, as noted, can be configuredas a touchscreen display. The student user 129A can contemporaneouslycorrectly pronounce the letter “A”, e.g. by entering voice data recordedas a voice clip that specifies the audio voice message (the voicemessage specifying the correct pronunciation for the letter “A”).Manager system 110 at block 1122 can return to block 1109 with thecurrent alphabet letter advance to the next successive letter in thealphabet for which associated to a current teaching session.

Referring to the loop of blocks 1109-1120, manager system 110 can beconfigured to iteratively provide prompting data to a student user andcan iteratively examine response data responsively defined by thestudent user. The prompting data can include first prompting data (block1109) for prompting a student user enter voice data defining a correctpronunciation for a certain letter, and second prompting data (block1113) prompting the student user to electronically enter handwrittendata defining a correct drawing of the certain letter. For each letterfor which a lesson is being provided, manager system 110 can berestricted from providing the second prompting data (prompting properletter formation) until manager system 110 determines by examination ofresponse data provided by voice data entered in response to the firstprompting data that the student user has correctly pronounced thecertain letter. In such manner focus of the user to an isolated segmentof a lesson is maintained so that the student user is able to betterretain the material of the lesson.

Referring to the loop of blocks 1109-1120, manager system 110 can beconfigured further to be restricted from prompting data associated to anext successive letter of a language alphabet relative to a certainletter until manager system 110 examining response data of a studentuser has determined that the student user has correctly (a) pronouncedthe certain letter in response to first prompting data prompting thestudent user to correctly pronounce the certain letter wherein the firstprompting data is absent of prompting data prompting the student user tocorrectly draw the certain letter (stage I), (b) drawn the certainletter in response to second prompting data prompting the student userto correctly pronounce the certain letter wherein the second promptingdata is absent of prompting data prompting the student user to correctlypronounce the certain letter (stage II), and (c) pronounced the certainletter while contemporaneously drawing the certain letter in response tothird prompting data wherein the third prompting data has prompted thestudent user to correctly pronounce the certain letter whilecontemporaneously correcting drawing the certain letter (stage III). Insuch manner focus of the user to an isolated segment of a lesson ismaintained so that the student user is able to better retain thematerial of the lesson.

FIG. 4R illustrates prompting data presented to user during a nextiteration of prompting data at block 1109 after manager system 110advances the current alphabet letter to a next successive alphabetletter associated to the current training session. The next successivealphabet letter relative to the letter “A” in the English language is“B”. Accordingly, prompting data sent during a next iteration of block1109 can include prompting data prompting the user, according to stage Iprocessing, to correctly enter an audio input specifying the correctpronunciation for the letter “B”. In response to prompting data sent atblock 1109, electronic teaching device 130A can present to a studentuser the received prompting data at block 1302.

Prompting data presented to a user as depicted in FIG. 4R, can includetext based prompting data and audio, e.g. synthesized voice basedprompting data. As shown in FIG. 4R, text based prompting data can bedisplayed on display 131D, e.g. there can be displayed as depicted inFIG. 4R the letter “B”, which the student user is being prompted topresent the correct pronunciation for. Accompanying the presentment ofthe text based data displayed on display 131D, electronic teachingdevice 130A can output an audio output message to prompt a student userto correctly pronounce the letter “B”. Such an output audio message caninclude the message “PLEASE SAY THE LETTER ‘B’”. In response to theprompting data the user can enter audio input data. The student userinput audio data can specify the correct pronunciation for the letter“B”. It will be seen during a next iteration of the loop comprisingblocks 1109-1119 can include manager system 110 determining that a userhas correctly entered an audio input recorded as a voice clip tocorrectly pronounce the letter “B” and responsively to a determinationthat a student user has presented correct pronunciation for the letter“B” can, at block 1113 send prompting data to prompt the student user tocorrectly electronically draw the letter “B”, in accordance with aselected stroke map, the selected stroke map for guiding the drawing ofthe letter “B” can be selected, like as in the case for the letter “A”can be selected from set of candidate stroke maps for the letter “B”,which candidate stroke maps can be obtained and stored in stroke maparea stroke map area 2123 based on, e.g. an examination ofelectronically entered handwritten data of social media system 150and/or by examination of configuration data defined by an administratoruser using a user interface such as user interface 3002, as described inconnection with FIG. 3B.

Candidate stroke maps for the letter “B” can specify different strokesequences for the letter “B”. For example, a first stroke map canspecify: (a) draw straight line down starting from the top left cornerto the lower look left corner; (b) draw a curved line starting from thetop left corner of the left line and terminating at the midpoint of theleft line; and (c) draw a curved line starting at the midpoint of theleft line and terminating at the lower left corner point of the leftline. Another stroke map for the letter “B” can specify, e.g. (a) draw acurved line commencing at the top left corner and terminating at a leftcenter point; (b) draw a rightward bulging curved line starting at theleft midpoint and terminating at the lower left corner; and (c) draw astraight vertical line upward from the lower left corner to the top leftcorner and connecting endpoints of the bulging curved lines of (a) and(b).

Throughout the course of manager system 110 running a training session,manager system 110 can iteratively determine whether an exit one or morecriterion has been satisfied. An exit one or more criterion can includesuch criterion as (a) that the student user has closed the electronicteaching device into a closed configuration is shown in FIG. 2A; or that(b) a timeout condition has occurred, i.e. that the student user has notresponded to prompting data within a time threshold period of time. Indecision blocks 1131-1133 manager system 110 can perform evaluating ofwhether an exit one or more criterion has been satisfied. On thedetermination that an exit one or more criterion has been satisfied,manager system 110 can proceed to block 1123.

At block 1123, manager system 110 can send session data for receipt andstorage by data repository 108 at block 1086. The session data stored atblock 1086 can be stored in history area 2124 of data repository 108.The session data stored at block 1086 can include performance data thatspecifies the performance of the student user during the just terminatedteaching session. Performance data can specify, e.g. whether the studentuser correctly pronounced a letter, whether the student user correctlydrew a letter, and such success or failure performance data can bestored for each letter for which the student user received promptingdata during the just terminated teaching session. Performance datastored at block 1086 can include performance score data. For example,manager system 110 can assign performance score to a student user independence on the number of iterations of prompting data presented tostudent user prior to the student user correctly pronouncing letter orcorrectly drawing a letter. Manager system 110, for example, can assignthe highest performance score to the student user, where the studentuser correctly pronounces or draws a letter in response to only oneiteration of prompting data and can assign correspondingly lowerperformance scores where the student user correctly pronounces or drawsa letter but in response to additional one or more iterations promptingdata. Manager system 110 can assign a lowest post performance score tostudent user, where the student user is unable to correctly pronounce ordraw letter in response to a maximum number of iterations of promptingdata.

Session data sent at block 1123 and stored at block 1086 can alsoinclude termination point session data that specifies the point of atraining session at which the training session was just terminated. Thetermination point data can specify, e.g. the alphabet letter which thestudent user is currently receiving prompting data for at the time ofthe termination of the just terminated teaching session.

With respect to the loop of blocks 1108-1123, embodiments hereinrecognize that manager system 110 can be performing multiple instancesof a teaching session described herein contemporaneously andsimultaneously, wherein each different teaching session can beassociated to a different student user. Embodiments herein furtherrecognize that the receiving and storing of blocks 1086 can be performedfor each teaching session mediated by manager system 110 over the courseof deployment of system 100. Thus, there can be stored in history area2124 session data for all teaching sessions mediated by manager system110 over the course of the deployment of system 100 over time, which caninclude multiple teaching sessions for each of multiple differentstudent users. In response to completion of block 1123 manager system110 can proceed to block 1124.

At block 1124, manager system 110 can perform machine learning trainingof one or more predictive model stored in models area 2126 of datarepository 108. Aspects of predictive model which can be subject totraining with use of training data at machine learning training block1124 is described in FIG. 5A and 5B. On completion of block 1124 managersystem 110 can proceed to block 1125. At block 1125, manager system 110can return to block 1101.

Referring to FIG. 5A, there is shown predictive model 5002 predictivemodel 5002, according to one embodiment, as shown in FIG. 5A can betrained with training data so that predictive model 5002 is configuredto return predictions as to a predicted performance of a user inresponse to the student user being subjected to prompting data inaccordance with a certain stroke map. As set forth herein manager system110, when providing student user prompting data prompting a user tocorrectly draw a certain alphabet letter, can select from can select onestroke map from a set of candidate stroke maps and the prompting datafor prompting the student user to correctly draw the certain letter canbe prompting data in accordance with the stroke sequence defined withinthe selected stroke map.

Predictive model 5002 as set forth in FIG. 5A can be trained withtraining data so that predictive model 5002 can be used for selection ofone stroke map out of a set of candidate stroke maps and the selectedstroke map can be used for guiding a student user to correctly draw analphabet letter. According to one embodiment, manager system 110 atblock 1113 can use predictive model 5002 for sending prompting data forprompting a user to correctly draw an alphabet letter. Use of predictivemodel 5002 in such a scenario is now described. Predictive model 5002can be trained with training data, so that predictive model 5002 oncetrained, is able to respond to query data to return predictedperformance data specifying predicted performance of a student user inresponse to the student user being presented with prompting data,prompting the user to correctly draw an alphabet letter in accordancewith a select certain stroke map. Query data for querying predictivemodel 5002 can include stroke map data and skill level data for theuser.

In one scenario, there can be K candidate stroke maps for a givenalphabet letter for which the student user is receiving a lesson.Manager system 110 can query predictive model 5002 K times for each ofthe K candidate stroke maps for the letter. The query data comprisingstroke map data can be accompanied by skill level data that determines askill level for the student user associated to a current trainingsession. Queried, as described predictive model 5002 can returnpredicted performance data for each of the K different stroke maps forthe certain alphabet letter. Manager system 110 can select a stroke mapreturning the best predicted performance data as the selected stroke mapfor use in prompting the user with prompting data at block 1113.

The skill level of a student user can be determined in multiple ways.For example, the skill level of a student user can be determined byexamining the performance data of the student user during teachingsessions. According to one embodiment, skill level data for a studentuser can be determined using teaching session performance data only forportions of the teaching session that are maintained constant for allstudent users over the course of deployment of system 100. According toone embodiment, skill level data can be inferred, e.g. based on age orgrade level of the student user. According to one embodiment, skilllevel can be based on a combination of performance data of the user andinferred skill level of the user based on, e.g. age or grade level.According to one embodiment, the skill level of the student user can bean inferred skill level during an initial training session of the user,but over time the skill level data can be provided to be increasinglydependent on performance data of the student user.

Manager system 110 can perform training of predictive model 5002. Atblock 1124, manager system 110 can apply iterations of training datasetsto predictive model 5002 and once predictive model 5002 has been trainedwith sufficient amounts for training data, predictive model 5002 can becapable of returning predictions with a threshold exceeding level ofconfidence. Training datasets for training of predictive model 5002 canbe applied after each teaching session mediated by manager system 110for all users of system 100. As depicted in FIG. 5A, a training datasetcan include stroke map data for an alphabet letter, skill level data forthe student user associated to the session teaching lesson, andperformance data for the student user associated to the completedteaching session. Predictive model 5002 once trained with iterations oftraining dataset is able to learn relationships between stroke map datafor a teaching session, skill level data, and performance data in amanner so that predictive model 5002, once sufficiently trained, is ableto return predictions for the performance prediction specifyingpredicted performance data for a student user in dependence on candidatestroke map data and skill level data for the student user. Thus, inresponse to query data that includes candidate stroke map data and skilllevel data, predictive model 5002 is able to predict performance datafor the student user and therefore is able to select one stroke map froma set of candidate maps based on the one stroke map being predicted toreturn the best performance data for the student user.

Manager system 110 can perform training of predictive model 5012.Predictive model 5012 is similar to predictive model 5002 for use inselecting a best performing stroke map except predictive model 5012 canbe used for predicting best a performing prompting profile. Managersystem 110 can be adapted to deploy different prompting profiles todifferent student users, the different prompting profiles defining bydifferent sets of prompting data (e.g. characterized by having differentgraphics, different delay times, different prompting data sequences,different audio prompts, and the like). According to one embodiment,data defining prompting profiles can be stored in languages area 2122and there can be stored in languages area data defining a plurality ofprompting profiles for each language supported. Manager system 110 cantrain predictive model 5012 with use of machine learning processes sothat predictive model 5012 learns best performing prompting profilesover time. At block 1124, manager system 110 can apply iterations oftraining datasets to predictive model 5012 and once predictive model5012 has been trained with sufficient amounts for training data,predictive model 5012 can be capable of returning predictions with athreshold exceeding level of confidence. Training datasets for trainingof predictive model 5012 can be applied after each teaching sessionmediated by manager system 110 for all users of system 100. As depictedin FIG. 5B, a training dataset can include prompting profile data for analphabet letter, skill level data for the student user associated to thesession teaching lesson, and performance data for the student userassociated to the completed teaching session.

Predictive model 5012 once trained with iterations of training datasetis able to learn relationships between prompting profiles for a teachingsession, skill level data, and performance data in a manner so thatpredictive model 5012, once sufficiently trained, is able to returnpredictions for the performance prediction specifying predictedperformance data for a student user in dependence on candidate promptingprofiles and skill level data for the student user. Thus, in response toquery data that includes candidate prompting profile and skill leveldata, predictive model 5012 is able to predict performance data for thestudent user and therefore is able to select prompting profile from aset of candidate prompting profiles based on the one prompting profilebeing predicted to return the best performance data for the studentuser. Manager system 110 at block 1109 prior to sending prompting dataassociated to a new letter of a teaching session can query predictivemodel 5012 multiple times referencing different candidate promptingprofiles to return a prediction as to the best performing promptingprofile and can select the predicted best performing candidate promptingprofile as the selected prompting profile selected for deployment.

With use of predictive model 5002, system 100 is able to adapt over timein different ways in dependence on recorded historical data for users ofsystem 100, over the course of a plurality of teaching sessions. Withuse of the predict of predictive model 5002, as shown in FIG. 5A,manager system 110 is able to deploy a plurality of stroke maps thatrespectively define different stroke sequences for formation of analphabet letter. Manager system 110, based on performance dataassociated to deployments of different stroke maps, is able to discernwith use of predictive model 5002 the best performing stroke map for aletter out of a set of candidate stroke maps, wherein the bestperforming stroke map is the stroke map predicted to return the optimalperformance data for a student user. System 100, accordingly, is able toadapt its operation based on historical data of a plurality of users sothat system 100 provides prompting data to student users in ways thatwill optimally teach the student users.

With use of predictive model 5012, system 100 is able to adapt over timein different ways in dependence on recorded historical data for users ofsystem 100, over the course of a plurality of teaching sessions. Managersystem 110 according to one embodiment can deploy a plurality ofprompting profiles and can apply performance data resulting from thedifferent deployments as training data for training predictive model5012 so that predictive model 5012 is configured for use in selecting abest performing prompting data. Manager system 110, based on performancedata associated to deployments of different prompting profiles is ableto discern with use of predictive model 5012 the best performingprompting profile out of a set of prompting profiles, wherein thepredicted best performing prompting profile is the prompting profilepredicted to return the optimal performance data for a student user.System 100, accordingly, is able to adapt its operation based onhistorical data of a plurality of users so that system 100 providesprompting data to student users in ways that will optimally teach thestudent users.

Various available tools, libraries, and/or services can be utilized forimplementation of predictive model 5002 and/or predictive model 5012.For example, a machine learning service can provide access to librariesand executable code for support of machine learning functions. A machinelearning service can provide access set of REST APIs that can be calledfrom any programming language and that permit the integration ofpredictive analytics into any application. Enabled REST APIs can providee.g. retrieval of metadata for a given predictive model, deployment ofmodels and management of deployed models, online deployment, scoring,batch deployment, stream deployment, monitoring and retraining deployedmodels. According to one possible implementation, a machine learningservice provided by IBM® WATSON® can provide access to libraries ofAPACHE® SPARK® and IBM® SPSS® (IBM® WATSON® and SPSS® are registeredtrademarks of International Business Machines Corporation and APACHE ®and SPARK ® are registered trademarks of the Apache Software Foundation.A machine learning service provided by IBM® WATSON® can provide accessset of REST APIs that can be called from any programming language andthat permit the integration of predictive analytics into anyapplication. Enabled REST APIs can provide e.g. retrieval of metadatafor a given predictive model, deployment of models and management ofdeployed models, online deployment, scoring, batch deployment, streamdeployment, monitoring and retraining deployed models. Trainingpredictive model 5002 and/or predictive model 5012 can include use ofe.g. support vector machines (SVM), Bayesian networks, neural networksand/or other machine learning technologies.

Education translates into job opportunities for economically challengedfamilies and holds the promise to alleviate them from poverty. With themeagre means to sustain their livelihood, such families can ill-afford aformal education for their children, especially so in remote locations.Attempts at addressing the basic literacy gaps have been focused onbuilding devices that are high on cost. Alternate methods such asclassroom teaching are costly from a dependency standpoint when requiredfor remote locations. Further, existing methods require end userintervention which increases room for error-prone learning. Also,existing methods rely on excessive communication which may become aburden to/demotivate the end-user.

Embodiments herein can provide audio messages instructing the user infollowing the outline elements and evaluates the same as well. Aconcluding audio message can identify an alphabet letter, instructs inits phonetic pronunciation, and provides a word-identification of thepicture of the exemplary article, thereby enhancing the user'svocabulary.

Embodiments herein can commence a teaching session with presentment ofthe first letter of the alphabet which is displayed on the left screenand progresses to the subsequent letters based on progress achieved,automatically. This ensures that the child learns the alphabet exactlyin the sequence required.

Embodiments herein can provide a visible indicator at the point thatline needs to be stroked for formation of a letter and progressivelymoving the visible indicator in the correct direction to indicate thecorrect formation of a letter. The indicator can be e.g. a dot or arrow.The indicator can include a highlight, e.g. can be presented in flashingform, brightened form, or in a certain color. This visual cue worksbetter since it is attractive to the child as it blinks and also doesnot require a level of audio comprehension for the child to understandinstructions.

Embodiments herein can be configured to first ensure that a child speaksthe letter correctly, and then, teaches the child to write inconjunction with speech.

Embodiments herein can be configured to only show the letter in thealphabet that needs to be read, outputs voice on how it should bespoken, accepts voice input from user, analyzes it, and providesfeedback to a user. The proposed method can provide an interface toteach the user to write the same letter once spoken correctly.

Embodiments herein can focus on teaching the letters of the alphabet inspoken and written form and then extends this to words.

Embodiments herein can provide visual hints and voice based instructionsto the end user towards learning letters of the alphabet. Embodimentscan start with a) teaching the end user how to speak a letter, and b)can follow it up with teaching how to write the same letter accompaniedwith speech. One focus of the proposed solution is on vernacularlanguages in particular. One focus of the proposed solution is onenabling people living in remote areas, e.g., children and other studentusers to be able to read and write in their mother tongue (the primarylanguage of communication) as well as other additional languages asrequired.

As part of a) the device initially displays a letter on the display-onlyscreen and lends a voice indicating how to speak the letter. The voiceinput received from the user is analyzed for correctness. Once the inputis correct, step b) is applied wherein the cursive path for the letteris demonstrated on the second (touch) screen and the user is promptedfor input. The input received is analyzed and feedback provided. Oncethe user successfully completes the cursive writing of the letter, thesame is repeated along with voice, until accuracy is obtained. The abovecan be extended to words once the basic alphabet has been successfullycompleted.

Embodiments herein can provide visual hints and voice based instructionsto the end user towards learning letters of the alphabet. It starts witha) teaching the end user how to speak a letter, and b) follows it upwith teaching how to write the same letter accompanied with speech. Thedevice according to one embodiment can be shaped like a spiral boundbook comprising 2 pages. Once opened, the dimension of the device maymatch the size of a A4 page.

The device (henceforth called ‘main device’) according to one embodimentcan comprise the following: (A) 2 screens: 1 display-only screen, andanother e-paper based touch screen. (B) a pair of magnetic clips whichare affixed to the bottom of the screens in order to hold them togetherwhen the main device is in closed form, (C) a RASPBERRY® Pi® device withcase attached to the back of the main device.

According to one embodiment, the device can run in first and secondmodes: I. Admin mode, II. Normal mode. The proposed method can includethe device first run in admin mode. Once the main device is connectedusing Bluetooth/USB, it switches to admin mode. Following is a set ofsteps in admin mode: 1. Connect Bluetooth/USB. 2. Admin chooses thelanguage. 3. Import/Load vocabulary for chosen language. 4. Load strokemap for chosen language. Each letter has a stroke map (sequence ofstrokes to be applied). 5. Load pronunciation for chosen language. 6.Load tones (cries) of a common set of animals. 7. Create profile (firsttime) for user. a. with user name, b. user input timeout, c. contactresume timeout. d. the name of the user's favorite animal (one among thepreloaded options) of the user and persist in SD card. 8. DisconnectBluetooth/USB.

The above steps can be achieved with the main device in closed position(and the device flipped over). 1. Open main device. 2. User hearswelcome message including the user's name (as saved in step 6 of adminmode above). The message is spoken mimicking the tone of the user'sfavorite animal (as saved in step 6.d of admin mode above). 3. User seesthe first letter on the left (display only) screen, 4. User hears avoice speaking the letter. 5. Main device waits for 5 seconds (userinput timeout value which is configurable) for user input. If no voiceinput is received, then sequence repeats from step 3. 6. Once voiceinput is received, it is analyzed using software regarding thecorrectness of the pronunciation. 7. If pronunciation is incorrect, usersees a half smile on the left screen, and sequence repeats from step 3.8. If pronunciation is correct, user sees a smile on the left screen,and a congratulatory message. The congratulatory message includes theuser's name. 9. User hears a message that writing will now be taught. Onthe left screen, the letter is displayed again. 10. On the right touchscreen, a dotted line representation is shown for the letter. The dottedline slowly converts into a bold line following the strokes for writingthe letter. 11. Once the entire letter on the touch screen turns intobold, user hears the letter once again. 12. Now, the dotted linerepresentation shows up again with a blinking dot at the start of theletter. Only the first stroke of the letter is shown. A voice promptsthe user by name to write. 13. If the user fails to touch the screen upto 5 seconds (user input timeout value), steps 10 through 12 repeat.This continues until the user touches screen at the blinking dot. Oncethe first stroke is completed, the next stroke shows up in dotted linewith a blinking dot at the start of the new stroke. This repeats foreach stroke in sequence until all strokes are completed. 14. The usermay complete moving the finger on the entire letter (finishing theentire dotted line). Lifting the finger and not resuming contact withthe touch screen in 10 seconds (contact resume timeout value which isconfigurable) is indicative of attempt completion. 15. At this stage theattempt is compared against the original on 2 counts: a. the writing hasto be complete. b. The strokes have to be applied exactly in the samesequence as expected (stroke map of the letter is compared). 16. Thelast known correct point on the dotted line is identified and the dotnow blinks at that point with a blinking arrow indicating the directionto proceed, and a voice prompt to the user (including the user's name)to start again. Step 14 through 16 repeat until the comparison is aperfect match for 15. a. and b. 17. Once the writing is complete, onlystep 8 repeats. 18. Now a message is heard with the user name whichindicates that writing and speaking have to be done together. Thedifference in this sequence is that at the end of writing the letter,user has to say the letter as well. 19. Once the writing and speakingtogether works fine, step 8 repeats. A message indicates that the userhas now learnt the first letter, and congratulates the user by name. 20.Steps 3 through 19 repeat for subsequent letters automatically as perthe sequence of letters in the alphabet. 21. If at any point the usercloses the main device, the magnetic strips snap the device shut. At thesame time, all the data associated with the user are persisted in theprofile previously created by admin on the SD card. 22. The persisteddata may include the following: a. User name b. Number of speechattempts for correct pronunciation. c. Number of writing attempts (i.Type of failure per writing attempt [incomplete/incorrect strokes]. ii.Time taken for completing each attempt). d. Number of writing-and-speechattempts (i. Type of failure per attempt [incomplete/incorrect strokes],ii. Time taken for completing each attempt, iii Time gap between writingcompletion and speech).

There can be 2 steps where comparisons are done: 1. Step 6 where thepronunciation in the voice of the user is compared against the original.This can be achieved using automatic pronunciation checker software. 2.Step 15 where the written output of the user is compared against theoriginal. Image recognition software can be applied in order to achievethe same.

Certain embodiments herein may offer technical computing advantagesinvolving computing advantages to address problems arising the realm ofcomputer systems and computer networks. Embodiments herein can provideimproved computer system operation in the realm of computer systemshaving user interface functionalities to provide teaching lessons tousers. Embodiments herein can predict, with use of ArtificialIntelligence (AI) processes, optimally performing prompting data andbased on AI based action decisions can provide predicted optimallyperforming prompting data to users. Embodiments herein can storehistorical data for a plurality of users returned over a plurality ofteaching sessions. Embodiments herein can use such historical data toreturn action decisions such as action decisions for the selection ofone stroke map from a set of candidate stroke maps, wherein eachcandidate stroke map specifies a different set of stroke sequences forthe formation of an alphabet letter. Embodiments herein can include useof a predictive model which can be trained using machine learningprocesses. Embodiments herein can include querying of a trainedpredictive model for return of predictions specifying the predictedperformance of a student user in response to the student user receivingparticular prompting data and with use of the described predictive modeloptimally performing prompting data can be selected for providing to astudent user.

FIGS. 6-8 depict various aspects of computing, including a computersystem and cloud computing, in accordance with one or more aspects setforth herein.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 6, a schematic of an example of a computing nodeis shown. Computing node 10 is only one example of a computing nodesuitable for use as a cloud computing node and is not intended tosuggest any limitation as to the scope of use or functionality ofembodiments of the invention described herein. Regardless, computingnode 10 is capable of being implemented and/or performing any of thefunctionality set forth hereinabove. Computing node 10 can beimplemented as a cloud computing node in a cloud computing environment,or can be implemented as a computing node in a computing environmentother than a cloud computing environment.

In computing node 10 there is a computer system 12, which is operationalwith numerous other general purpose or special purpose computing systemenvironments or configurations. Examples of well-known computingsystems, environments, and/or configurations that may be suitable foruse with computer system 12 include, but are not limited to, personalcomputer systems, server computer systems, thin clients, thick clients,hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network PCs, minicomputer systems, mainframe computersystems, and distributed cloud computing environments that include anyof the above systems or devices, and the like.

Computer system 12 may be described in the general context of computersystem-executable instructions, such as program processes, beingexecuted by a computer system. Generally, program processes may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program processes may belocated in both local and remote computer system storage media includingmemory storage devices.

As shown in FIG. 6, computer system 12 in computing node 10 is shown inthe form of a computing device. The components of computer system 12 mayinclude, but are not limited to, one or more processor 16, a systemmemory 28, and a bus 18 that couples various system components includingsystem memory 28 to processor 16. In one embodiment, computing node 10is a computing node of a non-cloud computing environment. In oneembodiment, computing node 10 is a computing node of a cloud computingenvironment as set forth herein in connection with FIGS. 7-8.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system 12 typically includes a variety of computer systemreadable media. Such media may be any available media that is accessibleby computer system 12, and it includes both volatile and non-volatilemedia, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program processes that are configured to carry out thefunctions of embodiments of the invention.

One or more program 40, having a set (at least one) of program processes42, may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram processes, and program data. One or more program 40 includingprogram processes 42 can generally carry out the functions set forthherein. In one embodiment, manager system 110 can include one or morecomputing node 10 and can include one or more program 40 for performingfunctions described with reference to manager system 110 as set forth inthe flowchart of FIG. 3A. In one embodiment, one or more electronicteaching device 130A-130Z can include one or more computing node 10 andcan include one or more program 40 for performing functions describedwith reference to electronic teaching device 130A-130Z as set forth inthe flowchart of FIG. 3A. In one embodiment, systems 140, 150 caninclude one or more computing node 10 and can include one or moreprogram 40 for performing functions described with reference to systems140, 150 as set forth in the flowchart of FIG. 3A. In one embodiment,administrator client computer device 120 can include one or morecomputing node 10 and can include one or more program 40 for performingfunctions described with reference to administrator client computerdevice 125 as set forth in the flowchart of FIG. 3A. In one embodiment,the computing node based systems and devices depicted in FIG. 1 caninclude one or more program for performing function described withreference to such computing node based systems and devices.

Computer system 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computer system12; and/or any devices (e.g., network card, modem, etc.) that enablecomputer system 12 to communicate with one or more other computingdevices. Such communication can occur via Input/Output (I/O) interfaces22. Still yet, computer system 12 can communicate with one or morenetworks such as a local area network (LAN), a general wide area network(WAN), and/or a public network (e.g., the Internet) via network adapter20. As depicted, network adapter 20 communicates with the othercomponents of computer system 12 via bus 18. It should be understoodthat although not shown, other hardware and/or software components couldbe used in conjunction with computer system 12. Examples include, butare not limited to: microcode, device drivers, redundant processingunits, external disk drive arrays, RAID systems, tape drives, and dataarchival storage systems, etc. In addition to or in place of havingexternal devices 14 and display 24, which can be configured to provideuser interface functionality, computing node 10 in one embodiment caninclude one or more output device 25 e.g. provided by a display or audiooutput device connected to bus 18. In one embodiment, output device 25can be configured as a touch screen display and can be configured toprovide user interface functionality, e.g. can facilitate virtualkeyboard functionality and input of total data. Computer system 12 inone embodiment can also include one or more sensor device 27 connectedto bus 18. One or more sensor device 27 can alternatively be connectedthrough I/O interface(s) 22. One or more sensor device 27 can include aGlobal Positioning Sensor (GPS) device in one embodiment and can beconfigured to provide a location of computing node 10. In oneembodiment, one or more sensor device 27 can alternatively or inaddition include, e.g., one or more of a camera, a gyroscope, atemperature sensor, a humidity sensor, a pulse sensor, a blood pressure(bp) sensor or an audio input device. Computer system 12 can include oneor more network adapter 20. In FIG. 7 computing node 10 is described asbeing implemented in a cloud computing environment and accordingly isreferred to as a cloud computing node in the context of FIG. 7.

Referring now to FIG. 7, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 7 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 8, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 7) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 8 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and processing components 96 for languageteaching herein. The processing components 96 can be implemented withuse of one or more program 40 described in FIG. 6.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a computer, or other programmable data processing apparatusto produce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks. These computerreadable program instructions may also be stored in a computer readablestorage medium that can direct a computer, a programmable dataprocessing apparatus, and/or other devices to function in a particularmanner, such that the computer readable storage medium havinginstructions stored therein comprises an article of manufactureincluding instructions which implement aspects of the function/actspecified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be accomplished as one step, executed concurrently,substantially concurrently, in a partially or wholly temporallyoverlapping manner, or the blocks may sometimes be executed in thereverse order, depending upon the functionality involved. It will alsobe noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used herein, thesingular forms “a,” “an,” and “the” are intended to include the pluralforms as well, unless the context clearly indicates otherwise. It willbe further understood that the terms “comprise” (and any form ofcomprise, such as “comprises” and “comprising”), “have” (and any form ofhave, such as “has” and “having”), “include” (and any form of include,such as “includes” and “including”), and “contain” (and any form ofcontain, such as “contains” and “containing”) are open-ended linkingverbs. As a result, a method or device that “comprises,” “has,”“includes,” or “contains” one or more steps or elements possesses thoseone or more steps or elements, but is not limited to possessing onlythose one or more steps or elements. Likewise, a step of a method or anelement of a device that “comprises,” “has,” “includes,” or “contains”one or more features possesses those one or more features, but is notlimited to possessing only those one or more features. Forms of the term“based on” herein encompass relationships where an element is partiallybased on as well as relationships where an element is entirely based on.Methods, products and systems described as having a certain number ofelements can be practiced with less than or greater than the certainnumber of elements. Furthermore, a device or structure that isconfigured in a certain way is configured in at least that way, but mayalso be configured in ways that are not listed.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below, if any, areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description set forth herein has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the disclosure. Theembodiment was chosen and described in order to best explain theprinciples of one or more aspects set forth herein and the practicalapplication, and to enable others of ordinary skill in the art tounderstand one or more aspects as described herein for variousembodiments with various modifications as are suited to the particularuse contemplated.

What is claimed is:
 1. A computer implemented method comprising:providing to a student user prompting data, wherein the prompting dataprompts the student user to enter into an electronic teaching devicevoice data defining a correct pronunciation for a certain alphabetletter of a language alphabet, and wherein the prompting data promptsthe student user to electronically enter handwritten data into theelectronic teaching device defining a correct drawing of the certainalphabet letter; examining response data received from the student userin response to the prompting data; and based on the examining indicatingthat the student user has correctly pronounced and drawn the certainalphabet letter, providing to the student user next prompting data,wherein the next prompting data prompts the student user to correctlypronounce a next alphabet letter, wherein the next prompting dataprompts the student user to correctly draw the next alphabet letter, thenext alphabet letter being successive to the certain alphabet letter inthe language alphabet.
 2. The computer implemented method of claim 1,wherein the prompting data includes pronunciation prompting data thatprompts for correct pronunciation of the alphabet letter, and drawingpronunciation data that prompts for correct drawing of the certainalphabet letter, wherein the examining response data includes examiningvoice response data received from the student user in response to thepronunciation prompting data, wherein the method includes providing thedrawing prompting data based on the examining voice response dataindicating that the student user has correctly pronounced the certainalphabet letter.
 3. The computer implemented method of claim 1, whereinthe prompting data includes drawing prompting data for the certainalphabet letter that prompts for correct drawing of the certain alphabetletter, wherein method includes selecting the drawing prompting datafrom candidate drawing prompting data for the certain alphabet letter,wherein the selecting is in response to a query of a predictive modelthat predicts best performing drawing prompting data, wherein thepredictive model has been training with use of training data obtainedfrom historical teaching sessions, which historical teaching sessionsincludes historical reaching sessions associated to users other than thestudent user.
 4. The computer implemented method of claim 1, wherein theprompting data includes drawing prompting data for the certain alphabetletter that prompts for correct drawing of the certain alphabet letter,wherein method includes selecting the drawing prompting data fromcandidate drawing prompting data for the certain alphabet letter,wherein the selecting is in response to a query of a predictive modelthat predicts best performing drawing prompting data, wherein thepredictive model has been trained with use of training data obtainedfrom historical teaching sessions, which historical teaching sessionsincludes historical teaching sessions associated to users other than thestudent user, wherein training data for training of the predictive modelincludes for respective ones of a plurality of historical teachingssessions, stroke map data specifying an identifier for the stroke mapused for generating letter formation prompting data for the historicalteaching session, skill level of a user associated to the historicalteaching session, and results data associated to the historical teachingsession.
 5. The computer implemented method of claim 1, wherein theprompting data includes drawing prompting data for the certain alphabetletter that prompts for correct drawing of the certain alphabet letter,and wherein presentation of the drawing prompting data to the studentuser includes a succession of a screen displays being presented to thestudent user, wherein succession of the screen displays graphicallydepict growth of a line of the certain alphabet letter over time toillustrate correct drawing for the line.
 6. The computer implementedmethod of claim 1, wherein the providing prompting data includesproviding prompting data so that a visible indicator displayed ondisplay of the electronic teaching device viewed by the student userprogressively moves responsively to the student user advancing thedrawing of a letter line for the formation of the certain alphabetletter so that the visible indicator iteratively prompts the user byindicating to the user a next position to which the letter linecurrently being drawn needs to be advanced for correct completion ofdrawing of the letter line currently being drawn by the student user. 7.The computer implemented method of claim 1, wherein the electronicteaching device includes a first page defining a panel in which a firstdisplay is disposed, and a second page defining a second panel in whicha second display is disposed, wherein the electronic teaching device isconfigured to be manually moved between a closed configuration and anopen configuration, wherein the electronic teaching device is configuredso that that when the electronic teaching device is in the openconfiguration the first display and the second display are visible tothe student user.
 8. The computer implemented method of claim 1, whereinthe electronic teaching device includes a first page defining a panel inwhich a first display is disposed, and a second page defining a secondpanel in which a second display is disposed, wherein the electronicteaching device is configured to be manually moved between a closedconfiguration and an open configuration, wherein the electronic teachingdevice is configured so that that when the electronic teaching device isin the open configuration the first display and the second display arevisible to the student user, wherein the method includes automaticallyinitiating a teaching session in response to a determination that thestudent user has manually moved the electronic teaching device into theopen configuration.
 9. The computer implemented method of claim 1,wherein the method includes restricting the providing of the nextprompting data to the student user unless the examining the responsedata indicates that the student user has correctly pronounced and drawnthe certain letter.
 10. The computer implemented method of claim 1,wherein the prompting data includes first prompting data for prompting astudent user enter voice data defining a correct pronunciation for acertain letter, and second prompting data for prompting the student userto electronically enter handwritten data defining a correct drawing ofthe certain letter, wherein the method includes restricting theproviding of the second prompting data to the student user for thecertain alphabet letter unless the examining the response data indicatesthat the student user has correctly pronounced the certain alphabetletter in response to the first prompting data.
 11. The computerimplemented method of claim 1, wherein the method includes determining askill level of the student user in dependence on the examining of theresponse data and selecting a certain stroke map out of set of candidatestroke maps for the next alphabet letter stored in a data repository foruse in generating the next prompting data, wherein the selecting acertain stroke map is in dependence on the skill level, wherein one ormore characteristic of the next prompting data is in dependence on whichof the candidate stroke maps is selected as the certain stroke map,wherein respective stroke maps of the candidate stroke maps specify asequence of strokes for the formation of the next alphabet letter. 12.The computer implemented method of claim 1, wherein the method includesdetermining a skill level of the student user in dependence on theexamining of the response data and selecting a certain stroke map out ofset of candidate stroke maps for the next alphabet letter stored in adata repository for use in generating the next prompting data, whereinthe selecting a certain stroke map is in dependence on the skill level,wherein one or more characteristic of the next prompting data is independence on which of the candidate stroke maps is selected as thecertain stroke map, wherein respective stroke maps of the candidatestroke maps specify a sequence of strokes for the formation of the nextalphabet letter, wherein the selecting a certain stroke map includesquerying a predictive model to return data indicating predictedperformance of respective ones of the set of candidate stroke maps, andidentifying the predicted best performing stroke map out of the set ofcandidate stroke maps, wherein the predictive model has been trainedwith use of training data stored in the data repository which has beenobtained from historical teaching sessions, which historical teachingsessions includes historical teaching sessions associated to users otherthan the student user, wherein training data for training of thepredictive model includes for respective ones of a plurality ofhistorical teachings sessions, stroke map data specifying an identifierfor the stroke map used for generating letter formation prompting datafor the historical teaching session, skill level of a user associated tothe historical teaching session, and results data associated to thehistorical teaching session.
 13. The computer implemented method ofclaim 1, wherein the method includes determining a skill level of thestudent user in dependence on the examining of the response data andselecting a certain prompting profile out of set of candidate promptingprofiles for the next alphabet letter stored in a data repository foruse in generating the next prompting data, wherein the selecting acertain prompting profile is in dependence on the skill level, whereincharacteristics of the next prompting data are in dependence on which ofthe candidate prompting profiles is selected as the certain promptingprofile, wherein respective prompting profiles of the candidateprompting profiles specify characteristics of the next prompting data tobe providing to the student user to prompt the student user tocorrecting pronounce and draw the next alphabet letter, wherein theselecting a certain prompting profile includes querying a predictivemodel to return data indicating predicted performance of respective onesof the set of candidate prompting profiles, and identifying thepredicted best performing prompting profile out of the set of candidateprompting profiles, wherein the predictive model has been trained withuse of training data stored in the data repository which has beenobtained from historical teaching sessions, which historical teachingsessions include historical teaching sessions associated to users otherthan the student user, wherein training data for training of thepredictive model includes for respective ones of a plurality ofhistorical teachings sessions, prompting profile data specifying anidentifier for the prompting profile used for generating prompting datafor the historical teaching session, skill level of a user associated tothe historical teaching session, and results data associated to thehistorical teaching session.
 14. The computer implemented method ofclaim 1, wherein the electronic teaching device includes a first pagedefining a panel in which a first display is disposed, and a second pagedefining a second panel in which a second display is disposed, whereinthe electronic teaching device is configured to be manually movedbetween a closed configuration and an open configuration, wherein theelectronic teaching device is configured so that that when theelectronic teaching device is in the open configuration the firstdisplay and the second display are visible to the student user, whereinthe method includes automatically initiating a teaching session inresponse to a determination that the student user has manually moved theelectronic teaching device into the open configuration, wherein theprompting data includes drawing prompting data for the certain alphabetletter that prompts for correct drawing of the certain alphabet letter,and wherein presentation of the drawing prompting data to the studentuser includes a succession of a screen displays being presented to thestudent user, wherein succession of the screen displays graphicallydepict growth of a line of the certain alphabet letter over time toillustrate correct drawing for the line, wherein the providing promptingdata includes providing prompting data so that a visible indicatordisplayed on display of the electronic teaching device viewed by thestudent user progressively moves responsively to the student useradvancing the drawing of a letter line for the formation of the certainalphabet letter so that the visible indicator iteratively prompts theuser by indicating to the user a next position to which the letter linecurrently being drawn needs to be advanced for correct completion ofdrawing of the letter line currently being drawn by the student user.15. The computer implemented method of claim 1, wherein the electronicteaching device includes a first page defining a panel in which a firstdisplay is disposed, and a second page defining a second panel in whicha second display is disposed, wherein the electronic teaching device isconfigured to be manually moved between a closed configuration and anopen configuration, wherein the electronic teaching device is configuredso that that when the electronic teaching device is in the openconfiguration the first display and the second display are visible tothe student user, wherein the method includes automatically initiating ateaching session in response to a determination that the student userhas manually moved the electronic teaching device into the openconfiguration, wherein the prompting data includes drawing promptingdata for the certain alphabet letter that prompts for correct drawing ofthe certain alphabet letter, and wherein presentation of the drawingprompting data to the student user includes a succession of a screendisplays being presented to the student user, wherein succession of thescreen displays graphically depict growth of a line of the certainalphabet letter over time to illustrate correct drawing for the line,wherein the providing prompting data includes providing prompting dataso that a visible indicator displayed on display of the electronicteaching device viewed by the student user progressively movesresponsively to the student user advancing the drawing of a letter linefor the formation of the certain alphabet letter so that the visibleindicator iteratively prompts the user by indicating to the user a nextposition to which the letter line currently being drawn needs to beadvanced for correct completion of drawing of the letter line currentlybeing drawn by the student user, wherein the method includes restrictingthe providing of the next prompting data to the student user unless theexamining the response data indicates that the student user hascorrectly pronounced and drawn the certain letter, wherein the promptingdata includes first prompting data for prompting a student user entervoice data defining a correct pronunciation for a certain letter, andsecond prompting data for prompting the student user to electronicallyenter handwritten data defining a correct drawing of the certain letter,wherein the method includes restricting the providing of the secondprompting data to the student user for the certain alphabet letterunless the examining the response data indicates that the student userhas correctly pronounced the certain alphabet letter in response to thefirst prompting data.
 16. The computer implemented method of claim 1,wherein the electronic teaching device includes a first page defining apanel in which a first display is disposed, and a second page defining asecond panel in which a second display is disposed, wherein theelectronic teaching device is configured to be manually moved between aclosed configuration and an open configuration, wherein the electronicteaching device is configured so that that when the electronic teachingdevice is in the open configuration the first display and the seconddisplay are visible to the student user, wherein the first display is adisplay only display and the second display is an e paper display,wherein the method includes automatically initiating a teaching sessionin response to a determination that the student user has manually movedthe electronic teaching device into the open configuration, wherein theprompting data includes drawing prompting data for the certain alphabetletter that prompts for correct drawing of the certain alphabet letter,and wherein presentation of the drawing prompting data to the studentuser includes a succession of a screen displays being presented to thestudent user, wherein succession of the screen displays graphicallydepict growth of a line of the certain alphabet letter over time toillustrate correct drawing for the line, wherein the providing promptingdata includes providing prompting data so that a visible indicatorprovided by a flashing dot displayed on display of the electronicteaching device viewed by the student user progressively movesresponsively to the student user advancing the drawing of a letter linefor the formation of the certain alphabet letter so that the visibleindicator iteratively prompts the user by indicating to the user a nextposition to which the letter line currently being drawn needs to beadvanced for correct completion of drawing of the letter line currentlybeing drawn by the student user, wherein the method includes restrictingthe providing of the next prompting data to the student user unless theexamining the response data indicates that the student user hascorrectly pronounced and drawn the certain letter, wherein the promptingdata includes first prompting data for prompting a student user entervoice data defining a correct pronunciation for a certain letter, andsecond prompting data for prompting the student user to electronicallyenter handwritten data defining a correct drawing of the certain letter,wherein the method includes restricting the providing of the secondprompting data to the student user for the certain alphabet letterunless the examining the response data indicates that the student userhas correctly pronounced the certain alphabet letter in response to thefirst prompting data, wherein the providing of the prompting data is independence on an examining of historical data of a data repository, theexamining includes examining of historical teaching sessions involvingstudent users other than the certain student user.
 17. The computerimplemented method of claim 1, wherein the electronic teaching deviceincludes a first page defining a panel in which a first display isdisposed, and a second page defining a second panel in which a seconddisplay is disposed, wherein the electronic teaching device isconfigured to be manually moved between a closed configuration and anopen configuration, wherein the electronic teaching device is configuredso that that when the electronic teaching device is in the openconfiguration the first display and the second display are visible tothe student user, wherein the first display is a display only displayand the second display is an e paper display, wherein the methodincludes automatically initiating a teaching session in response to adetermination that the student user has manually moved the electronicteaching device into the open configuration, wherein the prompting dataincludes drawing prompting data for the certain alphabet letter thatprompts for correct drawing of the certain alphabet letter, and whereinpresentation of the drawing prompting data to the student user includesa succession of a screen displays being presented to the student user,wherein succession of the screen displays graphically depict growth of aline of the certain alphabet letter over time to illustrate correctdrawing for the line, wherein the providing prompting data includesproviding prompting data so that a visible indicator provided by aflashing dot displayed on display of the electronic teaching deviceviewed by the student user progressively moves responsively to thestudent user advancing the drawing of a letter line for the formation ofthe certain alphabet letter so that the visible indicator iterativelyprompts the user by indicating to the user a next position to which theletter line currently being drawn needs to be advanced for correctcompletion of drawing of the letter line currently being drawn by thestudent user, wherein the method includes restricting the providing ofthe next prompting data to the student user unless the examining theresponse data indicates that the student user has correctly pronouncedand drawn the certain letter, wherein the prompting data includes firstprompting data for prompting a student user enter voice data defining acorrect pronunciation for a certain letter, and second prompting datafor prompting the student user to electronically enter handwritten datadefining a correct drawing of the certain letter, wherein the methodincludes restricting the providing of the second prompting data to thestudent user for the certain alphabet letter unless the examining theresponse data indicates that the student user has correctly pronouncedthe certain alphabet letter in response to the first prompting data,wherein the providing of the prompting data is in dependence on anexamining of historical data of a data repository, the examiningincludes examining of historical teaching sessions involving studentusers other than the certain student user, wherein the method includesdetermining a skill level of the student user in dependence on theexamining of the response data and selecting a certain stroke map out ofset of candidate stroke maps for the next alphabet letter stored in adata repository for use in generating the next prompting data, whereingenerating the candidate stroke maps include examining of electronicallyhandwritten data posted by a plurality of users into a social mediasystem, and examining of administrator user defined stroke map dataentered by an administrator user into a displayed user interface,wherein the selecting a certain stroke map is in dependence on the skilllevel, wherein one or more characteristic of the next prompting data isin dependence on which of the candidate stroke maps is selected as thecertain stroke map, wherein respective stroke maps of the candidatestroke maps specify a sequence of strokes for the formation of the nextalphabet letter, wherein the selecting a certain stroke map includesquerying a predictive model to return data indicating predictedperformance of respective ones of the set of candidate stroke maps, andidentifying the predicted best performing stroke map out of the set ofcandidate stroke maps, wherein the predictive model has been trainedwith use of training data stored in the data repository which has beenobtained from historical teaching sessions, which historical teachingsessions includes historical teaching sessions associated to users otherthan the student user, wherein training data for training of thepredictive model includes for respective ones of a plurality ofhistorical teachings sessions, stroke map data specifying an identifierfor the stroke map used for generating letter formation prompting datafor the historical teaching session, skill level of a user associated tothe historical teaching session, and results data associated to thehistorical teaching session.
 18. The computer implemented method ofclaim 1, wherein the electronic teaching device includes a first pagedefining a panel in which a first display is disposed, and a second pagedefining a second panel in which a second display is disposed, whereinthe electronic teaching device is configured to be manually movedbetween a closed configuration and an open configuration, wherein theelectronic teaching device is configured so that that when theelectronic teaching device is in the open configuration the firstdisplay and the second display are visible to the student user, whereinthe first display is a display only display and the second display is ane paper display, wherein the method includes automatically initiating ateaching session in response to a determination that the student userhas manually moved the electronic teaching device into the openconfiguration, wherein the prompting data includes drawing promptingdata for the certain alphabet letter that prompts for correct drawing ofthe certain alphabet letter, and wherein presentation of the drawingprompting data to the student user includes a succession of a screendisplays being presented to the student user, wherein succession of thescreen displays graphically depict growth of a line of the certainalphabet letter over time to illustrate correct drawing for the line,wherein the providing prompting data includes providing prompting dataso that a visible indicator provided by a flashing dot displayed ondisplay of the electronic teaching device viewed by the student userprogressively moves responsively to the student user advancing thedrawing of a letter line for the formation of the certain alphabetletter so that the visible indicator iteratively prompts the user byindicating to the user a next position to which the letter linecurrently being drawn needs to be advanced for correct completion ofdrawing of the letter line currently being drawn by the student user,wherein the method includes restricting the providing of the nextprompting data to the student user unless the examining the responsedata indicates that the student user has correctly pronounced and drawnthe certain letter, wherein the prompting data includes first promptingdata for prompting a student user enter voice data defining a correctpronunciation for a certain letter, and second prompting data forprompting the student user to electronically enter handwritten datadefining a correct drawing of the certain letter, wherein the methodincludes restricting the providing of the second prompting data to thestudent user for the certain alphabet letter unless the examining theresponse data indicates that the student user has correctly pronouncedthe certain alphabet letter in response to the first prompting data,wherein the providing of the prompting data is in dependence on anexamining of historical data of a data repository, the examiningincludes examining of historical teaching sessions involving studentusers other than the certain student user, wherein the method includesdetermining a skill level of the student user in dependence on theexamining of the response data and selecting a certain stroke map out ofset of candidate stroke maps for the next alphabet letter stored in adata repository for use in generating the next prompting data, whereinthe selecting a certain stroke map is in dependence on the skill level,wherein one or more characteristic of the next prompting data is independence on which of the candidate stroke maps is selected as thecertain stroke map, wherein respective stroke maps of the candidatestroke maps specify a sequence of strokes for the formation of the nextalphabet letter, wherein the selecting a certain stroke map includesquerying a predictive model to return data indicating predictedperformance of respective ones of the set of candidate stroke maps, andidentifying the predicted best performing stroke map out of the set ofcandidate stroke maps, wherein the predictive model has been trainedwith use of training data stored in the data repository which has beenobtained from historical teaching sessions, which historical teachingsessions includes historical teaching sessions associated to users otherthan the student user, wherein training data for training of thepredictive model includes for respective ones of a plurality ofhistorical teachings sessions, stroke map data specifying an identifierfor the stroke map used for generating letter formation prompting datafor the historical teaching session, skill level of a user associated tothe historical teaching session, and results data associated to thehistorical teaching session, wherein the method includes selecting acertain prompting profile out of set of candidate prompting profiles forthe next alphabet letter stored in the data repository for use ingenerating the next prompting data, wherein the selecting a certainprompting profile is in dependence on the skill level, whereincharacteristics of the next prompting data are in dependence on which ofthe candidate prompting profiles is selected as the certain promptingprofile, wherein respective prompting profiles of the candidateprompting profiles specify characteristics of the next prompting data tobe providing to the student user to prompt the student user tocorrecting pronounce and draw the next alphabet letter, wherein theselecting a certain prompting profile includes querying a secondpredictive model to return data indicating predicted performance ofrespective ones of the set of candidate prompting profiles, andidentifying the predicted best performing prompting profile out of theset of candidate prompting profiles, wherein the second predictive modelhas been trained with use of training data stored in the data repositorywhich has been obtained from historical teaching sessions, whichhistorical teaching sessions include historical teaching sessionsassociated to users other than the student user, wherein training datafor training of the second predictive model includes for respective onesof a plurality of historical teachings sessions, prompting profile dataspecifying an identifier for the prompting profile used for generatingprompting data for the historical teaching session, skill level of auser associated to the historical teaching session, and results dataassociated to the historical teaching session.
 19. A computer programproduct comprising: a computer readable storage medium readable by oneor more processing circuit and storing instructions for execution by oneor more processor for performing a method comprising: providing to astudent user prompting data, wherein the prompting data prompts thestudent user to enter into an electronic teaching device voice datadefining a correct pronunciation for a certain alphabet letter of alanguage alphabet, and wherein the prompting data prompts the studentuser to electronically enter handwritten data into the electronicteaching device defining a correct drawing of the certain alphabetletter; examining response data received from the student user inresponse to the prompting data; and based on the examining indicatingthat the student user has correctly pronounced and drawn the certainalphabet letter, providing to the student user next prompting data,wherein the next prompting data prompts the student user to correctlypronounce a next alphabet letter, wherein the next prompting dataprompts the student user to correctly draw the next alphabet letter, thenext alphabet letter being successive to the certain alphabet letter inthe language alphabet.
 20. A system comprising: a memory; at least oneprocessor in communication with the memory; and program instructionsexecutable by one or more processor via the memory to perform a methodcomprising: providing to a student user prompting data, wherein theprompting data prompts the student user to enter into an electronicteaching device voice data defining a correct pronunciation for acertain alphabet letter of a language alphabet, and wherein theprompting data prompts the student user to electronically enterhandwritten data into the electronic teaching device defining a correctdrawing of the certain alphabet letter; examining response data receivedfrom the student user in response to the prompting data; and based onthe examining indicating that the student user has correctly pronouncedand drawn the certain alphabet letter, providing to the student usernext prompting data, wherein the next prompting data prompts the studentuser to correctly pronounce a next alphabet letter, wherein the nextprompting data prompts the student user to correctly draw the nextalphabet letter, the next alphabet letter being successive to thecertain alphabet letter in the language alphabet.